Download Avhandling 20130902 Ulla-Britt Diamant

Umeå University Medical Dissertations, New Series 1583
Long QT Syndrome
- studies of diagnostic methods
Ulla-Britt Diamant
Department of Public Health and Clinical Medicine,
Medicine.
Umeå 2013
Responsible publisher under Swedish law: the Dean of the Medical Faculty
This work is protected by the Swedish Copyright Legislation (Act 1960:729)
ISBN: 978-91-7459-693-9
ISSN: 0346-6612
Cover: Wooden relief in basswood made by surolle ℅ Jögge Sundqvist. Part of
commisson work at Umeå University Hospital 2013.
Photographer: Jögge Sundqvist
Elektronic version available at http://umu.diva-portal.org/
Printed by: Print & Media
Umeå, Sweden 2013
To the study participants and their relatives
The Indian heart, as seen by the Ojibwa Indians, is full of strength
and beats powerfully in space.
The cover: Relief “I live by the clear space”
Artist Jögge Sundqvist.
i
Table of Contents
Table of Contents
ii
Abstract
iv
Abbreviations
v
Svensk sammanfattning
vii
List of papers
viii
Introduction
1
Background
2
Historical background
2
LQTS a genetic cardiac ion channelopathy - Genotype
4
Functional effects
5
Heredity in LQTS
6
Prevalence of LQTS
7
Genetic testing for LQTS
7
Founder mutations and founder populations
7
Clinical presentation of LQTS - Phenotype
Arrhythmias in the LQTS
8
8
Other ECG changes associated with LQTS
9
The “Schwartz score”
10
Risk stratification in the LQTS
11
Prophylactic treatment of symptoms in Long QT syndrome
11
Physiologic basis of the ventricular repolarization
12
Action potential of the ventricular myocytes in the normal heart
12
Prolonged action potential
13
Ventricular gradient
13
Heterogeneities of ventricular repolarization
14
Manual methods to define the end of the T-wave
15
“Normal” QT interval
16
The QT interval corrected for heart rate
18
The corrected QT interval and bundle branch block
18
Other clinical conditions associated with prolonged QT interval
19
Electrocardiographic recordings
19
Vectorcardiography
19
VCG loop characteristics
23
Other VCG parameters
25
Aims
27
Materials
28
Overview of the LQTS study population in paper I-IV
28
Subjects
28
Ethical considerations
30
ii
Methods
31
12-lead ECG
31
Automatic measuring and interpretation of the QT interval
31
Manual measurement of the QT interval
32
VCG according Frank lead system
32
Automatic measuring of the QT interval
32
Off-line analysis of the VCG
33
Genetic testing
33
Genealogy, geography and haplotype analysis
34
Genealogical and geographic analysis
34
Haplotype analysis
35
Mutation age and prevalence of the Y111C mutation in the KCNQ1 gene
36
Statistic methods
36
Limitations
37
Summary of Results
39
Paper I and II
39
Paper III
39
Paper IV
40
Discussion
43
Manual measurements
43
Automatic methods
44
QTc cut-off values
45
The “ideal” QT measurement
47
Electrophysiological phenotype
47
Ventricular repolarization
49
Risk markers
49
Founder population Y111C
50
Conclusion
51
Acknowledgements
52
References
54
Appendices
1
I - Instructions in manual measurement of the QT interval (translated)
2
II - Long QT syndrome questionnaire (translated)
3
iii
Abstract
Background: The Long QT Syndrome (LQTS) is a hereditary heart
disease with risk of malignant ventricular arrhythmia and sudden
cardiac death. Despite our increased knowledge about genotype and
phenotype correlation we still rely on the 12-lead ECG for assessment of
the QT interval and the T-wave morphology for diagnosis and risk
stratification. Intra- and -inter individual variability in manually QT
measurement and, e.g., difficulties in defining the end of the T-wave may
impair the diagnosis of LQTS. Increased heterogeneity in ventricular
repolarization (VR) may be an important factor in the arrhythmogenicity
in cases of LQTS. In a LQTS founder population the same mutation is
carried by numerous individuals in many families which provide a
unique opportunity to study diagnostic methods, risk assessment, VR
and the correlation between genotype and phenotype.
Methods: Resting 12-lead ECG and vectorcardiogram (VCG) were
recorded in 134 LQTS mutation carriers and 121 healthy controls, to
investigate the capability and precision in measuring the QT interval.
For assessment of the VR, VCG was compared in individuals with
mutations in the KCNQ1 and KCNH2 gene. Genealogical and geographic
studies were performed in 37 index cases and their relatives to
determine if Swedish carriers of the Y111C mutation in the KCNQ1 gene
constitute a founder population. To confirm kinship, haplotype analysis
was performed in 26 of the 37 index cases. The age and prevalence of the
Y111C mutation were calculated in families sharing a common haplotype
Results: VCG by automatic measurement of the QT interval provided
the best combination of sensitivity (90%) and specificity (89%) in the
diagnosis of LQTS. VCG showed no consistent pattern of increased VR
heterogeneity among KCNQ1 and KCNH2 mutation carriers. Living
carriers of the Y111C mutation shared a common genetic (haplotype),
genealogic and geographic origin. The age of the Y111C mutation was
approximately 600 years. The prevalence of living carriers of the Y111C
mutation in the mid-northern Sweden was estimated to 1:1,500-3,000.
Conclusion: We have shown that VCG provides a valuable contribution
to the diagnosis and risk assessment of LQTS in adults and children. No
consistent pattern of increased VR heterogeneity was found among the
LQTS mutation carriers. The identified Swedish LQTS founder
population will be a valuable source to future LQTS research and may
contribute to increase our understanding of LQTS and the correlation of
phenotype, genotype and modifying factors.
iv
Abbreviations
AP
APD
Bpm
EAD
ECG
LQTS
µV
µVs
Ms
QRSamplitude
QRSarea
QRS-T angle
Tamplitude
Tarea
Tavplan
Tazimuth
TdP
Teigenvalue
Televation
Tp-e
VCG
VG
Action potential from ventricular myocytes
Action potential duration
Beats per minute
Early after depolarization
Electrocardiogram
Long QT Syndrome
Microvolt
Microvolt seconds
Millisecond
Amplitude of the maximum QRS vector in
space
The spatial area under the curve formed by the
moving heart vector during the QJ interval
The angle between the maximum QRS and T
vectors
Amplitude of the maximum T vector in space
The spatial area under the curve formed by the
moving heart vector during the JT interval
The mean distance between the periphery of
the T loop and both sides of the preferential
plane
The angle of the maximum T vector in the
transverse plane (0◦ left, +90◦ front, -90◦ back
and 180◦ right)
Torsade de Pointes
The squared quotient between the two largest
perpendicular axes (eigenvalues) of the T loop
in the preferential plane [(d1/d2)2 where d1 ≥
d2]
The angle of the maximum T vector in the
cranio-caudal direction by us defined from 0◦
(caudal direction) to 180◦ (cranial direction)
T peak to T end, the last part of the QT interval
and final repolarization
Vectorcardiogram
Ventricular gradient or QRST area is the
spatial area under the curve formed by the
moving heart vector during the QT interval;
also the sum of the QRSarea vector and Tarea
vector, taking into account the angle between
v
VR
them; it describes the dispersion of action
potential
morphology
throughout
the
ventricles.
Ventricular repolarization
The intervals and waves in an ECG complex
vi
Svensk sammanfattning
Bakgrund och syfte med avhandlingen: Långt QT syndrom (LQTS) är
en ärftlig hjärtsjukdom med risk för plötslig död p.g.a. livshotande
hjärtrytmrubbning (kammartakykardi). EKG är ett viktigt instrument vid
diagnos och riskbedömning av LQTS. Avhandlingens syfte är att förbättra
diagnos och riskbedömning av LQTS genom att undersöka olika EKG
metoder, samt finna ut om svenska bärare av Y111C mutationen
(sjukdomsanlag) i KCNQ1 genen har samma ursprung och utgör en
founderpopulation. En founderpopulation utgör en genetisk homogen grupp
och är en viktig källa för framtida forskning av bl.a. diagnostiska metoder.
Metod och material: Registrering av 12 avlednings EKG och
vektorkardiogram (VKG) utfördes på 134 LQTS mutationsbärare- och 121
friska kontroller. Metodernas diagnostiska precision samt förmåga till
riskbedömning avseende LQTS värderades. Genealogiska och geografiska
studier utfördes på 37 indexpersoner och deras släktingar. Haplotypanalys
(släktskaps analys) utfördes på 26 av de 37 indexpersonerna.
Resultat: VKG erbjöd den bästa kombinationen av sensitivitet (0,90),
specificitet (0,89) för diagnos av LQTS. Genealogiska studier visade att 26
bärare av Y111C tillhörde samman släktträd med en anfader/moder som
levde för ca 400 år sedan. Alla nu levande bärare av Y111C visade sig ha ett
gemensamt geografiskt och genetiskt ursprung.
Slutsatser: Vi har visat att VKG är en effektiv metod med hög precision
som utgör ett värdefullt tillskott vid LQTS diagnostik. Avseende
riskmarkörer i LQTS populationen, fann vi vid VKG mätning förlängt QT
intervall men för övrigt normala fynd i repolarisationsprocessen. Vi har
identifierat den första svenska LQTS founderpopulationen som utgör en
viktig källa för framtida forskning.
Betydelse: För enskilda individer med risk för potentiellt livshotande
hjärtrytmrubbningar är tidig diagnostik, riskvärdering och profylaktisk
behandling av stor vikt. Vi har påvisat vektorkardiografins fördelar vilket
skulle kunna ge metoden en ökad betydelse i kliniken. Dock krävs ytterligare
studier för att befästa vektorkardiografins position vid diagnostik och
riskvärdering vid LQTS. Att vi identifierat en founderpopulation öppnar
unika möjligheter för internationell betydelsefull forskning inom ett snabbt
expanderande område. På sikt kommer detta att kunna bidra till minskad
dödlighet bland patientgrupper med LQTS.
vii
List of papers
This thesis is based on the following papers, which are referred to in the text
by their Roman numerals:
I
Two automatic QT algorithms compared with manual
measurement in identification of long QT syndrome
Diamant UB, Winbo A, Stattin EL, Rydberg A, Kesek M,
Jensen SM
J Electrocardiol. 2010 Jan-Feb;43(1):25-30
Reproduced with kind permission from Elsevier.
II
Vectorcardiographic Recordings of the Q-T Interval in a
Pediatric Long Q-T Syndrome Population
Diamant UB, Jensen SM, Winbo A, Stattin EL, Rydberg A
Pediatr Cardiol. 2013 Feb;34(2):245-9
Reproduced with kind permission from Springer Science and
Business Media
III
Electrophysiological Phenotype in the LQTS Mutations Y111C
and R518X in the KCNQ1 Gene
Diamant UB*, Farzad Vahedi*, Winbo A, Rydberg A, Stattin
EL, Jensen SM, Bergfeldt L
*both authors contributed equally
Manuscript
IV
Origin of the Swedish long QT syndrome Y111C/KCNQ1
founder mutation
Winbo A, Diamant UB, Rydberg A, Persson J, Jensen SM,
Stattin EL
Heart Rhythm. 2011 Apr;8(4):541-7.
Reproduced with kind permission from Elsevier
viii
Introduction
The Long QT Syndrome (LQTS) is a hereditary heart disease that has been
further clarified in the era of molecular genetics. The electrocardiogram
(ECG) is still one of the most important elements in the description of the
clinical phenotype in LQTS, in spite of the increased knowledge about
genotype and phenotype correlation. In the daily work of diagnosis and risk
stratification, we still rely on the 12-lead ECG for the evaluation of the
duration of the QT interval and the T-wave morphology. However, because
of pitfalls in the manual measurement of the QT interval, the diagnosis of
LQTS may be misclassified due to, e.g., difficulties in defining the end of the
T-wave. There are also intra- and inter- individual differences in
measurements of the QT interval (1), which further worsens the accuracy of
manual measurements. The ECG is fundamental in determining the
diagnosis and in the risk stratification of LQTS. Nonetheless, there is no
consensus on how to measure the QT interval or how to correct the QT
interval for heart rate.
The aim of this thesis was to improve the capability of ECG as a diagnostic
and prognostic tool in LQTS. Paper I and II compare two automatic methods
(12-lead ECG and Frank vectorcardiogram VCG) and manual measurement
of the QT interval in healthy individuals and a population of LQTS subjects.
In paper I we also state intra- and inter- variability of manual QT
measurement for four observers. Promising results in the automatic
measurement of the QT interval by VCG are included in paper I and II, which
deals with the time-consuming and error-prone manual measurement of the
QT interval. Increased ventricular repolarization (VR) heterogeneity may be
an important factor in the arrhythmogenicity in LQTS. This has, to the best
of our knowledge, not been evaluated in humans in any previous study. In
paper III, VR was studied in two populations with two different LQTS
mutations and a group of healthy individuals. Genetic homogeneous
populations are of great value to develop and improve diagnostic methods
and risk assessment tools. A so-called founder population - comprising
individuals with a common geographic and genealogic origin and carrying a
common mutation - is ideal for studies of correlation between genotype and
phenotype including ventricular repolarization. During our work in the
LQTS clinic we noticed a high number of families carrying the same
mutation Y111C in the KCNQ1 gene. After systematic genealogic and genetic
studies, presented in paper IV, we proved that these families formed a LQTS
founder population.
1
Background
Historical background
The first ECG in a human was recorded by Augustus Waller in 1887 (2).
Later William Einthoven invented the string galvanometer and named the
wave deflections P, Q, R, S and T (3), instead of ABCD that had been used
with the capillary electrometer. He avoided N and O, which were already in
use with mathematic/geometric matters and started with P to label the first
deflection. In 1912, he also defined the current standard ECG leads I, II and
III also known as “Einthoven’s triangle” (4). Einthoven and colleagues
described the first electrical heart vector and the angle that was between a
horizontal reference line and the heart vector. It was time consuming to
calculate the loop, since each lead (I,II and III) had to be aligned manually
for the calculation of the loop in the frontal plane (5). The study of
orthogonal leads became easier, and was further developed with the
introduction of the cathode-ray oscillograf in the 1950´s. More than 30
corrected lead systems was developed but the Frank lead system became the
most frequently used because it was a compromise between accuracy and
practical manageability (6). With today’s computer technology, it is easy to
record a VCG with presentation of the loops in real-time. During the 1930´s
the augmented limb leads (aVR, aVF and aVL) and the precordial leads (V1V6) came into use and in the 1950´s the use of the standard 12 lead ECG was
widely spread. In 1930´s the American Heart Association and the Cardiac
Society of Great Britain defined the standard positions and wiring of the 12lead ECG, which today forms the basis of manual and automatic
interpretation of ECG - one of the most important diagnostic tools for
cardiac diseases (7, 8).
Congenital LQTS is a cardiac arrhythmogenic disorder associated with
prolongation of the QT interval on the ECG, syncope and sudden cardiac
death in young individuals with no structural heart disease. It was first
described by Jervell and Lange-Nielsen 1957 in a family with congenital
deafness, prolonged QT interval, syncope and sudden death transmitted in a
autosomal recessive pattern (9). Romano reported in 1963 (10) and Ward in
1964 (11) a similar syndrome but without deafness and transmitted in an
autosomal dominant way. In 1991 came the first report that presented LQTS
as a genetic disorder, a finding that was achieved after gene linkage studies.
The study was performed in a pedigree with both healthy and LQTS affected
relatives, and uncovered a strong linkage between LQTS and a DNA marker
at the Harvey ras-1 locus on chromosome 11 (12). In 1995, the connection
between gene mutations and cardiac potassium and sodium channels was
2
discovered – since then LQTS has been considered as a cardiac ion
channelopathy (13, 14). The early use of comprehensive national population
records in Sweden provides good opportunities to track the ancestry of living
persons back in time - this registration is a golden source for mapping of
monogenetic diseases (15). Following a church law of 1686, the priests were
enjoined since the late 17th and early 18th century to register in church
archives every dweller in their parish. As a result of this we now, in Sweden,
possess registers of all individual habitants of the Swedish parishes in the
catechetical examination records. These were replaced in 1895-1900 by the
“congregation book” which, in its turn, was abolished in 1991. The church
registered all migration, births, deaths and marriages, and from 1860 every
tenth year census were held and archived in the Swedish Central Bureau of
Statistics. Tracking the geographical origin of the population carrying the
Y111C mutation in the KCNQ1 gene brought us to the area along Ångerman
River valley and its tributaries. As the other historical provinces of Northern
Sweden, the landscape Ångermanland was first populated in the coastal
areas and the river valleys (16). Occasional Swedish settlements were
founded during the middle ages in the area where our founder couple settled
in the mid-17th century. During the 16th, century there was also some
colonization in the area by settlers coming from Finland. The settlers were
principally farmers, but they also provided for themselves by hunting and
fishing. There was a Sami indigenous population in the area that was
predominantly nomads, living by keeping reindeers, hunting and fishing.
The state encouraged the colonization of the interior of northern Sweden
through the so called “Lappmarksplakatet” of 1673, and this was the starting
point for the era of colonization of the inlands of northern Sweden that
lasted for over 200 years. No great influx from other parts of the country
occurred during the first half of the 18th century. In 1749, the Crown
supplemented the bill with the Lapplands regulations settling a distribution
of trades between the colonizers and the Sami natives. Settlers should
foremost pursue farming, wherewith the trades of hunting and fishing would
essentially be protected for the Sami. The main object of the regulations was
to stimulate colonization and the settlers were granted 15-25 years free of
taxation. The regulations didn’t accomplish any significant results towards
an increase in settlings until a few decades later. During the 19 th century,
there was an increase of immigration from other parts of the country, and
the population of the inland of northern Sweden grew. In the latter part of
the 19th century there was a surge in the commercial interests in forestry
affording new sources of income. The first half of the 20th century saw a
certain increase of movement from the river valleys to the coastal cities, but
not until after the 1950´s has there been a net decrease of population in the
studied area.
3
LQTS a genetic cardiac ion channelopathy - Genotype
LQTS is the most well-known monogenetic heart disease and several
hundreds of mutations in 13 genes have been described (Table 1). Most of
the mutations can be found in 3 genes, the KCNQ1 (40-55%), KCNH2 (3045%) and SCN5A gene (5-10%) (14, 17, 18). LQTS is mostly a heterogenetic
disease, meaning that each family carries a mutation unique for their family.
Table 1. LQTS genes.
Gene
Syndrome
Frequency
%
Functional effect
Phenotype (in
vitro)
KCNQ1 (LQT1)
RWS, JLNS 40-55
11p15.5
Loss-of-function
KCNH2 (LQT2)
RWS
30-45
7q35-36
Loss-of-function
SCN5A (LQT3)
RWS
5-10
3p21-p24 Gain-of-function
ANKB (LQT4)
RWS
<1
4q25-q27 Loss-of-function
KCNE1 (LQT5)
RWS, JLNS <1
21q22.1
Loss-of-function
KCNE2 (LQT6)
RWS
<1
21q22.1
Loss-of-function
KCNJ2 (LQT7)
AS
<1
17q23
Loss-of-function
CACNA1C (LQT8)
TS
<1
12p13.3
Gain-of-function
CAV3 (LQT9)
RWS
<1
3p25
Loss-of-function
SVN4B (LQT10)
RWS
<1
11q23.3
Loss-of-function
AKAP9 (LQT11)
RWS
<1
7q21-q22 Loss-of-function
SNTA1 (LQT12)
RWS
<1
20q11.2
Loss-of-function
KCNJ5 (LQT13)
RWS
<1
11q24
Loss-of-function
LQTS Long QT Syndrome, RWS Romano Ward Syndrome, JLNS Jervell and
Lange-Nielsen Syndrome, AS Andersen Syndrome, TS Timothy Syndrome.
Modified from (19).
4
Locus
Functional effects
Gene mutations cause changes in the proteins of the cardiac ion channels.
This creates a disturbance in the functional effect of the ion current through
the cell membrane (19) (Figure 1). The mutations can be divided according
to their phenotypical effects into different categories. A loss-of-function
mutation is a mutation that does not create any functional gene product. A
dominant loss-off-function mutation creates a defect gene product that
disturbs the normal functional effect of the wild-type gene. A gain-offunction mutation results in a gene product that has a new feature, most of
these mutations are dominant. A gain-of-function mutation can be due to a
new amino acid sequence which alters protein function. Moreover, it can be
a mutation in the regulatory regions, which expresses as a new tissue or in a
new stage where it has not previously been active (20).
The KCNQ1 gene (LQT1) encodes the α-subunit of the K+ channel that
generates the slow potassium current (IKs) (Figure 1) (21). During
sympathetic activation with increased heart rate the repolarization duration
is hastened by an increase of the IKs (19). When a KCNQ1 mutation causes
defective IKs the repolarization duration does not shorten appropriately to
sympathic stimulation. This can be seen in an ECG as a prolonged QT
interval that does not adapt properly to increased heart rate.
The KCNH2 gene (LQT2) encodes the α-subunit of the K+ channel and
thereby for the rapid potassium current (IKr). A mutation in this region
causes an effect similar to a mutation in the KCNQ1 gene with reduction of
outwardly IKr and thus a prolongation of the duration of the repolarization.
Both mutations in the KCNQ1 and KCNH2 gene reduces components of the
outwardly potassium current (IK) through the cardiac ion channels.
The third common gene causing LQTS is the SCN5A gene (LQT3) that
encodes the α-subunit of the cardiac sodium channel conducting the inward
sodium current under the depolarization. The result of a mutation in the
SCN5A gene produces an increase in the delayed Na+ inward current and the
consequence is a prolongation of the action potential (AP) of the cardiac
myocytes.
The result of all of these mutations in the different genes thus creates an
arrhythmogenic cardiac condition.
5
Figure 1: Illustration of the effect of altered ion-channel currents on the
ventricular action potential (AP) duration in LQTS. The direction of ion
currents: inward = below the line; outward = above the line. Hatched
rectangles = time location of the effect of mutations in LQT1, LQT2 and
LQT3 on sodium and potassium ion-channel currents. A prolonged AP is
seen when (horizontal arrow) there is an inappropriate gain of function
(GOF) in late sodium current (INa) or loss of function (LOF) in slowly (IKs) or
rapidly (IKr) acting repolarization potassium currents. Reprinted from (21).
Reproduced with kind permission from Elsevier.
Heredity in LQTS
Two hereditary variants of LQTS are known, the most common being
Romano-Ward syndrome (RWS). If one parent carries a mutation the risk is
50 % for each child to develop RWS – this hereditary pattern is known as
autosomal dominant. The other variant is Jervell and Lange-Nielsen
syndrome (JLNS) which is transmitted in an autosomal recessive way. When
both parents carry a mutation, the risk of each child inheriting the mutation
is 50% (RWS) and 25% to inherit both mutations and get the disorder JLNS
6
syndrome. JLNS is a serious disease and is in addition to cardiac
arrhythmias associated with congenital deafness (22).
Prevalence of LQTS
The prevalence of LQTS has gradually increased due to the growing use of
molecular genetic diagnostics which has consequently increased the number
of diagnosed asymptomatic carriers (23). The estimated prevalence has
increased from 1:10 000 in 2000 (24), to 1:5 000 in 2008 (25) and 1:2000 in
2009 (26). In paper IV, we present prevalence data from the area of midnorthern Sweden (counties of Jämtland, Västernorrland and Västerbotten)
of the first Swedish LQTS founder mutation Y111C in the KCNQ1 gene.
Genetic testing for LQTS
Genetic testing for the LQTS has entered routine clinical practice and is a
valuable instrument in the diagnosis of LQTS. An individual (index case)
with the clinical diagnosis LQTS can be offered genetic testing to identify the
mutation causing LQTS. Genetic testing identifies mutations in up to 75-80%
of clinical affected individuals (27). When a mutation is identified in a
family, this gives the first-degree relatives the opportunity to undergo
genotyping thus providing important information in guiding the
management of individuals.
Founder mutations and founder populations
A founder mutation can be described as a mutation that appears in a limited
gene pool in a population living in the same geographic area and thus being
enriched (15). Environmental factors, socio-ethnical constructions and
characteristics of the mutation itself affect the expression of the disease.
LQTS founder mutations have been found in South Africa (28) and Finland
(29). A population growth during the 17th century and onward made the
population in northern Sweden a breeding ground for the growth of
monogenetic diseases (15). The river valleys of northern Sweden running
from northwest to northeast has separated the populations living within the
river valleys from other populations. This has contributed to sub-isolates of
people living in the same geographic area within the river valleys. Moreover,
Sweden has a unique opportunity of genealogic studies via the
comprehensive population records which allows genealogical mapping of
monogenetic diseases in the population. A LQTS founder mutation with
large numbers of individuals provides an opportunity to study the genotypephenotype correlations and impact of modifying factors on the phenotype.
7
Clinical presentation of LQTS - Phenotype
The LQTS phenotype is diverse and may include syncope, sudden cardiac
death and an ECG with or without QT interval prolongation. Specific factors
have been showed to trigger syncopal episodes, where LQT1 patients are
more likely to develop cardiac events during exercise and swimming (30).
Emotions and sudden noise give rise to cardiac events in individuals affected
with mutations in the KCNH2 gene (LQT2), and LQT3 carriers can
experience events on awakening and during sleep. The family history of
syncope and sudden death among first-degree and second-degree relatives is
important in the initial evaluation of a patient with suspected LQTS.
Notably, about 30-50 % of the carriers of a LQTS mutation are asymptomatic
throughout life.
Arrhythmias in the LQTS
The ventricular arrhythmia associated with the cardiac events in LQTS is
Torsade de Pointes (TdP) (Figure 2). TdP is a polymorphic ventricular
tachycardia characterized by a gradual change in the amplitude and twisting
of the QRS complexes around the isoelectric line. The onset of the TdP is
often preceded by a short-long-short sequence in R-R intervals, with the last
sequence interrupting the T-wave (R on T phenomenon). In most of the
cases the TdP is self-terminating and causes palpitations and/or syncope,
but in the worst case the TdP degenerates into ventricular fibrillation (VF)
and causes cardiac arrest or sudden cardiac death (31).
Figure 2. ECG from a loop-recorder implanted in an 18 year old female with
unknown syncope episodes, showing the typical pattern seen in Torsade de
Pointes.
Experimental studies have shown that the abnormal prolongation of the AP
creates triggered activity, e.g., early after depolarizations (EAD), and the
abnormal dispersion of repolarization is the substrate that initiates and
8
perpetuates TdP (32-34). Why TdP stops or why it continues is not known. A
study in a LQTS population of 50 patients including 151 episodes of TdP,
showed that the majority of these episodes (56 %) and QT-related extra
systoles (70%) originated from the outflow tract (35). The outflow tract was
defined as the area inferior to the pulmonary and aortic valve and other
essentially contiguous structures, e.g., the right and left ventricular outflow
tracts, and areas superior to the mitral and tricuspid annulus.
Other ECG changes associated with LQTS
A prolonged QT interval has been shown to be associated with a high-grade
AV-block especially in children (36). T-wave alternans is a macroscopic
every-other-beat variation in T-waves and is a sign of a major electrical
instability, and identifies particular patients with high risk of malignant
arrhythmias (37) (Figure 3). In infants, subtle notches in the T-wave can be
normal. However, in adults these notches are not normal, and subtle
notched T-waves in lead II or V4-V6 should give suspicion of LQTS (38). It
has been recognized that a typical T-wave morphology may be associated
with specific genetic types. However, because there are overlaps in the Twave morphology between the affected genes, the T-wave morphology is
difficult to use in prediction of the affected gene in individuals with LQTS
(39).
Figure 3. Twenty-four hour Holter recording from an 11 year old boy with
Long QT syndrome showing T-wave macroscopic alternans.
9
The “Schwartz score”
The “Schwartz score” was presented in 1993 (updated 2011) and proposed as
a quantitative approach in the diagnosis of LQTS (Table 2) (19). The scoring
system evaluates not only the length on the QT interval but includes other
ECG findings together with clinical history and family history.
Table 2. LQTS Diagnostic Criteria Schwartz 2011
Points
Electrocardiographic
findings*
A
B
C
D
E
F
Clinical history
A
B
Family history
A
B
QTc **, ms
≥480
460-479
450-459 (men)
QTc** 4th minute of recovery from
exercise stress test ≥480
Torsade-de-Pointes***
T-wave alternans
Notched T-wave in 3 leads
Low heart rate for age ****
Syncope ***
With stress
Without stress
Congenital deafness
Family member with definite LQTS
*****
Unexplained SCD ‹30 year of age
among immediate family members
*****
3
2
1
1
2
1
1
0.5
2
1
0.5
1
0.5
LQTS long QT syndrome; *absence of medications or disorders known to
affect these electrocardiographic features; **QTc calculated by Bazett
formula QTc=QT√RR (RR in seconds); ***mutually exclusive; ****resting
heart rate below the second percentile for age;*****the same family
member cannot be counted in A and B.
Score: ≤1 point: low probability of LQTS; 1.5-3 points: intermediate
probability of LQTS; ≥3.5 points: high probability. Modified from (19).
10
Risk stratification in the LQTS
In the general LQTS population, and in particular in the LQT1 population
there is a higher risk of cardiac events until puberty in males, whereas
females has a higher risk during adulthood (40). Based on the probability of
a first cardiac event (syncope, cardiac arrest or sudden death) before the age
of 40, and without therapy it has been proposed a protocol for risk
stratification among patients with LQTS according to genotype and sex. For
instance, there is a high risk (≥ 50 %) if the QTc is ≥ 500 ms in a carrier of a
mutation in the KCNQ1 or KCNH2 gene or in a male carrier with a mutation
in the SCN5A gene (41). LQTS patients have variability in the QTc between
follow-up ECGs. The maximum QTc interval contain prognostic information
in addition to the baseline ECG, therefore it has been suggested in the risk
stratification of LQTS to always record follow-up ECGs (42).
Prophylactic treatment of symptoms in Long QT syndrome
With prophylactic medication and minor lifestyle changes it is possible to
effectively reduce mortality and morbidity in LQTS (43). It is thus important
to identify even asymptomatic individuals and for this we need accurate
diagnostic tools. ß-adrenergic blocking agents are the first choice in
prophylactic therapy of LQTS patients (43). This medication is most effective
in individuals with mutations in the KCNQ1 gene, but somewhat less
effective in KCNH2 gene (44). Many of the cardiac events during
prophylactic treatment are thought to be caused by non-compliance or use of
QT-prolonging drugs (45).
Implantable cardioverter defibrillator (ICD) is recommended in patients
with cardiac arrest (43, 46, 47). Left cardiac sympathetic denervation (LCSD)
may be used when prophylactic beta-blocking therapy has failed and/or were
there has been “storms” of repeated defibrillation because of TdP in subjects
with ICD (47).
11
Physiologic basis of the ventricular repolarization
Action potential of the ventricular myocytes in the normal heart
The cardiac action potential (AP) is divided in four different phases (48). The
cardiac AP of the cardiac myocytes is illustrated in the upper part of Figure
1. Phase 0; the rapid depolarization in the ventricular tissue, caused by the
rapid movement of Na+ (INa) through ion channels (when the membrane
potential is approximal -65 mV) into the intracellular spaces of the myocytes.
After just a few milliseconds the ion channels are inactivated and the
channels are closed. Phase 1; a slight repolarization, the upstroke of phase
0 activates the channels which causes the transient efflux of K+ from the
myocytes (“transient outward current” Ito). This brief repolarization phase is
rapidly over and is seen as a notch in the AP. Phase 2; the plateau phase,
this is the major determinant of the duration of the AP and is caused by the
inwardly depolarization of calcium currents (ICa) and the outwardly
repolarization of potassium currents (IK). The ion channels (L-type calcium
channels and potassium channels) have a slow activation rate and are
opened in connection to phase 0, the balance of inward and outward
currents between the competing ion channels determine the duration of the
plateau phase. Phase 3; inactivation of the depolarizing current of calcium
(ICa) is coupled to an increasing net outward potassium current (IK)
consisting of rapid (IKr) and slow (IKs) components of the delayed potassium
channels. Phase 4; during phase 4 the resting membrane potential is
restored (-90 mV) and the baseline potential is maintained by the inwardrectifier potassium current (IK1).
There are slight differences between the AP in the myocardium and the AP in
the Purkinje fibers in the ventricular conducting system. There is also a
subtle difference between the myocardial layers APs where the midmyocardium (M cells) having the longest action potential duration (APD)
(49). The duration of ventricular repolarization is longer in the endocardium
than the epicardium, and shorter in de basal regions compared with the apex
(50). This heterogeneity of repolarization is seen in healthy adult hearts.
The interval between the beginning of Q and end of T in a surface ECG is an
indirect measure of the duration of the ventricular action potentials (51)
(Figure 4). Measured on a surface ECG, the QT interval consists of two
parts, the QRS interval and the JT interval, which reflects the depolarization
(in the His-Purkinje system and ventricles) and the duration of the
repolarization, respectively. The depolarization is spread through the
12
Purkinje fibers from endocardium to epicardium and the repolarization is
synchronized in opposite direction from epicardium to endocardium.
Figure 4. The QT interval corresponds to the interval between the Q wave
and the end of the T-wave. When the QT interval is rate corrected (Bazett’s
formula) the preceding R-R interval (seconds) is used QTc=QT/(√RR).
Prolonged action potential
To maintain the correct balance between internal and external ion
concentrations, it is essential that the ion currents can flow through the cell
membrane of the myocytes. If there is an increase of the inward current or
decrease of the outward current during the repolarization, a prolonged AP
occurs (50). This will be reflected in the ECG and appears as a prolonged QT
interval with alterations of the ST segment and T-wave morphologies.
Abnormalities in the ST segment and T-wave of the QT interval can be
classified as primary or secondary repolarization abnormalities (52). In
absence of changes in the depolarization, the primary changes depend on
changes in the shape and/or the duration of the repolarization phase 3 of the
AP. Such changes may be caused by, e.g., ischemia, electrolyte abnormalities
(Ca++ and K+), myocarditis, ion channelopathies (e.g., LQTS) but also abrupt
changes in heart rate or body position. A change in the QRS that gives rise to
abnormalities in the ST segment and T-wave is called secondary
repolarization abnormalities. These may occur because of voltage gradients
and become manifest due to changes in the depolarization that alter the
repolarization. Secondary ST and T-wave abnormalities occur with bundlebranch blocks, ventricular pre-excitation and ectopic ventricular beats and
paced ventricular complexes.
Ventricular gradient
Wilson et al. introduced the concept ventricular gradient (VG) that deals
with primary versus secondary repolarization abnormalities (53, 54). The
QRST area in a single ECG lead reflects the summarized local electrical
activity in the myocardium, viewed from the angle of the particular ECGlead. Commonly the orthogonal leads X, Y and Z in a VCG are used, since the
13
QRST-areas in the X, Y and Z-leads, together with the angle between the
separate QRS and T areas, are used in the mathematical expression of the
VG. An abnormal T-wave axis with a normal QRS axis indicates primary
repolarization abnormalities. Secondary repolarization abnormalities, e.g., in
left bundle-branch block the ST and T-wave vectors changes in the opposite
direction of the mean QRS vector (52).
Heterogeneities of ventricular repolarization
The differences in the time-course of the repolarization between cells in
different myocardial layers (endocardium, mid-myocardium and
epicardium) contribute to the T-wave of the ECG (55). Voltage gradients,
developing as a result of the different time course of repolarization of phase
2 and 3 in cells of the three myocardial layers, give rise to opposing voltage
gradients on either side of the M region (mid-myocardium), which are in
large part responsible for the inscription of the T-wave (56). In an upright Twave, the earliest repolarization is seen in the epicardial cells and the latest
is in the AP of the M cells. Full repolarization of the epicardial cells´ AP and
the M cells´ AP, coincides with the peak of the T-wave and end of the Twave, respectively. Therefore, the duration of the M cells´ AP, determines
the QT interval, whereas, the duration of the epicardial AP determine the
QTpeak interval.
Heterogeneities of VR have long been associated with arrhythmogenesis.
Increase of the spatial heterogeneity (hereafter called dispersion) of
repolarization has been identified as the substrate of arrhythmias both in
LQTS and acquired LQTS (55). Triggered activity, which is both substrate
and trigger for TdP in LQTS, may be induced by EADs which in turn may be
induced by accentuated spatial dispersion secondary to an increase of the
transmural, trans-septal or apico-basal dispersion of repolarization (55).
Experimental models of LQT1, LQT2 and LQT3 have been developed from
canine arterially perfused left ventricular wedge preparations (57, 58). Such
studies suggests that the prolongation of the APD in the M cells leads to a
prolongation of the QT interval, as well as an increased transmural
dispersion of repolarization, both of which contributes to development of
TdP (59-61).
The Tpeak-Tend interval (T peak to T end, the last part of the QT interval and
final repolarization) has been proposed as an index of transmural dispersion
of repolarization (62). It has been shown that this interval is increased in
patients with LQTS (63). Tpeak-Tend have been suggested to have a potential
value in predicting the risk of developing TdP (30, 64-66). However, further
14
studies are needed to evaluate these indices of electrical dispersion and the
prognostic value in the assignment of arrhythmic risk.
Manual methods to define the end of the T-wave
It has been shown in several studies that the manual measurement of the QT
interval is bound to have errors because of the difficulties to define the end of
the T-wave. This leads to both intra observer variability and variability
between different observers.
The difficulty to identify the end of the T-wave may be amplified by a fusion
of the U-wave and the T-wave, by a T-wave that coincide with the following
P-wave (high heart rates), by a biphasic T-wave, and by low amplitudes of
the T-wave. There is also a problem to choose in which lead the QT interval
should be determined since no consensus has emerged among different
researchers. In paper I and II we used the method to define the end of the Twave that was described by Goldenberg (67) (Figure 4). This method was
proposed to be used in the day-to-day practice in the diagnosis of LQTS and
other repolarization disorders. The longest QT value from the mean of 3-5
ECG complexes in lead II and V5 or V6 should be used. As with other similar
methods, this may lead to elements of subjectivity, in particular when
biphasic T-waves and U-waves interrupt the return of the T-wave to the
baseline.
Another way to measure the QT interval, is by using the intersection of a
tangent to the steepest slope (“peak-slope”) of the last limb of the T-wave
and the baseline in lead II or V5 (Figure 5). The proponents of the tangent
method believe that it gives a greater consistency in the measurement of the
QT interval (68). When comparing the tangent method with the “threshold
method” (T-wave offset when the T-wave reaches the isoelectric baseline) in
healthy individuals with a normal T-waves, the tangent method gives shorter
QT interval by up to 10 ms (69). The tangent method provides longer QT
intervals than the threshold method when used in subjects with changed Twave morphology, flat T-waves and U-waves as seen in drug induced QT
prolongation (70).
15
Figure 4. A) Normal T-wave: T end is when the descending limb returns to
TP baseline. B) Separated T and U wave: T end is when the descending limb
of the T-wave returns to TP baseline before the onset of the U wave. C)
Biphasic T-wave: T1 and T2 with similar amplitude, T end is when T2 returns
to TP baseline. D) When a second low-amplitude interrupts the end of the
larger T-wave: T end can both be at the nadir (1) of the two waves and at the
final return to TP baseline (2) U wave? TP baseline corresponds to the
baseline between the end of the T-wave and the start of next P wave.
Modified from (67).
Figure 5. Tangent method: With a tangent drawn to the steepest slope in
the end of the T-wave in lead II or V5. The intersection between baseline and
the tangent is the end of the T-wave. The R to R interval is measured from
the preceding R-R interval.
“Normal” QT interval
Is the QTc normal? This is the question that we face every time we measure
and evaluate the QT interval. In two large population-based studies,
including 12,500 and 40,000 healthy individuals, the following normal
limits of QTc were suggested according to the 97.5th percentiles for the lower
16
and upper limits in healthy subjects: Adult males 350-450 milliseconds (ms)
and, for adult females 360-460 ms (71, 72). In the guidelines from
AHA/ACC/HRS QTc values ≥ 450 ms for men and ≥ 460 for women have
been stated as prolonged QT (52). For the diagnosis of LQTS, Sami Viskin
has proposed an upper limit for prolonged QTc ≥ 470 ms for males and
QTc ≥ 480 ms for females, even if the individual is asymptomatic and have a
negative family history (23). It is unusual that the LQTS diagnosis is based
only on a prolonged QTc - usually more evidence is required (73). The most
accepted QTc limits among both adults and children have been suggested by
Goldenberg et al. (67, 74) (Table 3). Goldenberg’s study further revealed a
difference in QTc depending on age and sex among adults. The QTc
difference depending on sex seems to disappear with old age (75).
Table 3. Bazett corrected QTc values for diagnosing QT prolongation
Children 1-15 y
(ms)
Normal QTc
Borderline QTc
Prolonged QTc
Modified from (67).
Adult male
(ms)
Adult female
(ms)
<440
<430
<450
440-460
430-450
450-470
>460
>450
>470
Other sources used to define limits for the QT interval are studies of
populations with genetically confirmed carriers and non-carriers of LQTS
mutations (76). Such studies have documented carriers with normal QTc as
well as non-carriers with prolonged QTc. It has been found that the
diagnostic criteria QTc ≥ 450 ms fails to identify 10% of the carriers and
incorrectly diagnose 10% of the non-carriers. It is known that the mutation
carriers with normal QTc account for about 36% of the LQT1 carriers, 19% of
the LQT2 carriers and 10% of the LQT3 carriers (41).
There is a pronounced diurnal variation of the QT interval in the normally
innervated heart. This follows changes in neurally mediated autonomic tone,
mainly parasympathetic, during sleep and on the circadian variation in
circulating catecholamines (77). It has been demonstrated in healthy
individuals that autonomic conditions, independent of the heart rate,
directly affects the ventricular myocardium and causes changes in the QT
interval, and this can complicate the clinical assessment (78).
17
The QT interval corrected for heart rate
In healthy individuals, the QT interval shortens with increasing R-R interval.
Therefore, it has become standard practice to use a correction formula, such
as the Bazett formula (79), to normalize the QT interval to a heart rate of 60
beats per minute (bpm), yielding the rate-corrected QT or QTc = QT/(√RR),
where RR is the preceding R-R interval in seconds. When using the Bazett
formula for heart rates below 60 bpm the QTc is somewhat overcorrected
resulting in too short QTc intervals (false-negative values). The opposite
takes place when correcting heart rates above 90 bpm, where Bazett´s
formula gives too long QT intervals (false-positive values) (67). In borderline
cases, it would be advisable to repeat the measurements during heart rate
> 60 bpm or < 90 bpm. The Fridericia formula (80) QTc=3√R-R has mostly
been used in children because it reflects a more accurate QTc in higher heart
rates, but it has the same limitations at slow heart rates as Bazett´s formula
(67). Numerous other formulas have been suggested that may give a more
uniform correction over a wide range of heart rates (48). However, the
Bazett and Fridericia formulas are the most frequently used because they
provide nearly equivalent results for the diagnosis of QT prolongation in
subjects with normal heart rate, i.e., between 60-90.
The relationship between the QT interval and the heart rate has a substantial
inter-subject variability and a strong intra-subject stability (81). It is also
known that the QT interval duration does not instantly adapts to heart rate
changes, since there is a lag time before the QT is stabilized phenomenon
known as QT-RR hysteresis (82, 83). The lag time has been shown to be
individual and is approximately 2 minutes (84), but may be prolonged in
cardiac disease and may be altered by autonomic perturbations (85).
The corrected QT interval and bundle branch block
In the left and right bundle branch-block (BBB) the excitation time is
prolonged and QT interval prolongation is induced. The easiest correction
would be to subtract 70 ms from the calculated QTc in case of left bundlebranch block (LBBB), or to subtract 40 ms in right bundle-branch block
(RBBB) (86). To detect prolonged repolarization in BBB, the JT interval or
Bazett’s QTc-QRS has been proposed (87). A study evaluating the previous
proposal was performed in 11,739 individuals with normal conduction and
1,251 individuals with BBB (88), but still there was a residual correlation
between the heart rate and the QT interval (r=0.54) in BBB, whereas the
residual correlation was r=0.32 in the group with normal conduction. When
comparing six different formulas for QT or JT correction in BBB in two
different groups at different heart rates, the Hodges formula [QTcH = QT +
18
1.75 (heart rate – 60)] was found to produce the smallest heart rate
dependency (89).
Other clinical conditions associated with prolonged QT
interval
There are other conditions than LQTS that are associated with a
prolongation of the QT interval and may cause TdP. Drugs commonly cause
the “acquired long QT syndrome”, e.g., certain antibiotics, some
antidepressants, antihistamines, diuretics, anti-arrhythmic drugs,
cholesterol-lowering drugs, diabetes medications and some antifungal and
antipsychotic (www.azcert.org). Also cardiac disorders such as chronic heart
failure, cardiomyopathies and bradycardia due to sinus dysfunction or as
mentioned, conduction block has been shown to prolong the QT interval. It
is not uncommon to find a prolonged QT interval in, e.g., people suffering of
anorexia-nervosa (90, 91), or subarachnoidal heamorrhage. Electrolyte
imbalance especially hypokalemia, hypo magnesaemia and hypocalcaemia, is
also a common cause of prolonged QT interval as well as intracoronary
contrast injection and resuscitation (32).
Electrocardiographic recordings
The electromotive forces of the heart can be recorded by two different
systems, the scalar and the vectorial system. The scalar system measures the
difference in the APs of the heart between two leads, a negative and a
positive on the body surface, or a positive on the body surface and a
constructed zero potential. The vectorial system presents the projection of
the electromotive forces of the heart viewed in three mutually perpendicular
directions. In addition to the differences in potential and speed, the
vectorcardiogram adds the direction of the electromotive forces.
Vectorcardiography
The clinical usefulness of vectorcardiography (VCG) is well documented. It
has advantages over the 12-lead ECG, in particular in describing the
increased dispersion in ventricular repolarization (VR) and the association to
T loop morphology (92-95). With a distinct stop, the end of the T-wave loop
is easy to detect with VCG compared with ECG. VCG also gives information
about the spatial orientation of the repolarization and also a more
19
anatomically reliable T vector loop, as compared to a 12-lead ECG. VCG
describes the variation in electrical activity in the heart as a single dipole. In
each moment of a heartbeat, a spatial vector with an arrowhead is depicted
representing the orientation and the magnitude (length of the vector) of the
dipole. When each instantaneous single vector is plotted consecutively in a
heartbeat, continuous vector loops are formed in space for each heartbeat. If
the configuration of all three loops in all three planes are analyzed
simultaneously, it is possible to calculate the vector magnitude by using the
direction and magnitude of the spatial vector (Pythagorean formula);
vector magnitude = √X2+Y2+Z2 (Figure 6).
Figure 6. The vector magnitude constructed from Frank leads X, Y and Z.
The interval between the letters Q and F correspond to the QT interval.
Reprinted from (96). Reproduced with permission from Elsevier.
20
From the three orthogonal leads X, Y and Z, the spatial VCG can be recorded
and projected. Ernest Frank developed a system to compensate for the nonspherical human torso and the eccentric origin of the heart’s electrical
activity. The three Frank orthogonal leads X, Y and Z are calculated from the
electrodes using the equation shown in (Figure 7) (6, 97, 98).
Figure 7. Frank lead system, with the 3 orthogonal leads X, Y, and Z
recorded by 8 electrodes. Reprinted from (96). Reproduced with permission
from Elsevier.
X = (0.610 × A) + (0.171 × C) − (0.781 × I)
Y = (0.655 × F) + (0.345 × M) − (1.000 × H)
Z = (0.133 × A) + (0.736 × M) − (0.264 × I) − (0.374 × E) − (0.231 × C).
21
If two of the three leads X, Y and Z are depicted in a coordinate system a
separate loop can be constructed for each ECG component P, QRS and Tloops and presented in three planes (Figure 8).
X; Y Frontal plane
X; Z Transversal plane (or horizontal)
Y; Z Sagittal plane
Figure 8. QRS and T loops calculated from leads X, Y, and Z. The upper
loops showing the QRS and T loop together, the lower only the T loop.
Reprinted from (96). Reproduced with permission from Elsevier.
22
VCG loop characteristics
The depolarization and repolarization of the heart can be described by
analyzing the direction, the morphology and the interrelationship between
the characteristics of each loop.
The T vector orientation with its maximum vector in space under the
repolarization is described in following parameters:

Tazimuth (◦) – is the angle in the transverse plane (X-Z). The angle is
0◦ when the vector is pointing to the left. Forward direction is
defined as 0-180◦ and backward direction as 0-(-180) (Figure 9) .

Televation (◦) –is the angle between the vector and the Y axis. It is 0◦
when the vector is pointing downwards and 180◦ when the vector is
pointing in the cranial direction (Figure 9).
Figure 9. Dotted line: T vector loop, dashed line arrow: maximum T vector
in space. A) Tazimuth expresses the angle in the transverse plane (X;Z)
vector pointing to the left 0˚, forward direction 0˚ to 180˚, backward
direction 0˚to -180˚. B) Televation expresses the angle between the T vector
and the Y-axis perpendicular to the transverse plane (0˚= vector pointing
downward, 180˚= vector pointing in the cranial direction). Reprinted from
(99). Reproduced with permission from Elsevier.
23
The QRS and T vector orientation and their interrelationship can be
described by the orientation of the maximum vector in space.

QRS – T vector angle (◦) – Maximal angle between the QRS and T
vector loop.
The morphology of the T vector loop can be described by Tavplan, Teigenv and
Tarea (93);
 Tavplan (µV) -is the mean distance between the sample values of the T
loop and its preferential plane, a measure of the T loops bulginess.
Increased dispersion of the repolarization is reflected as a high value
of the Tavplan (100) (Figure 10).
Figure 10. Tavplan (µV) expresses the bulginess of the T loop in relation to a
preferential plane; Tavplan can also be defined as the mean distance of the T
loop from the preferential plane. Reprinted from (101). Reproduced with
permission from Elsevier.

Teigenv (unitless) expresses the form and symmetry of the T loop by
the quotient between the two highest eigenvalues (≈ diameters; d1
and d2) of the matrix of inertia. T eigenv = d1/d2 where d1>d2,
Teigenv = 1 corresponds to a circular T loop (sign of increased
dispersion of the repolarization) and a higher value correspond to a
normal more elongated T loop. Teigenv can be described as the longest
axis (d1) of the T loop that can be rotated most easily and d2 is the
perpendicular axis to d1 that allows the easiest rotation. There is a
third perpendicular axis d3, but it has a value close to 0 and is
therefore negligible (Figure 11).
24
Figure 11. Teigenv (unitless) expresses the form and symmetry of the T loop
and is the quotient between the highest d1 and d2 (≈ diameters) of the T
loop. Reprinted from (101). Reproduced with permission from Elsevier.

Tarea (µVs) is the spatial area under the curve formed by the moving
heart vector during the J-Tend interval in X, Y and Z leads: (Tx2 + Ty2
+ Tz2)½ .

QRSarea (µVs) is the spatial area under the curve formed by the
moving heart vector during the Q-J interval in X, Y and Z leads:
½
(QRSx2 + QRSy2 + QRSz2) .
Other VCG parameters

Tp-e (ms) - Tpeak to Tend, the last part of the QT interval and final
repolarization in the QRST complex.

Ventricular Gradient (VG µVs) describes the dispersion of action
potential morphology throughout the ventricles, (Figure 12).
25
Figure 12. Ventricular Gradient (VG µVs). The spatial ventricular
gradient (VG) sometimes referred to as the QRSTarea is the vectorial sum of
the QRSarea and Tarea vectors, taking into account the angle between them.
VG = (QRSarea2 + Tarea2 + 2*QRSarea*Tarea*cosine)1/2.
 is the angle between the QRSarea vector and the Tarea vector (0° to 180°),
QRSarea and Tarea are the spatial areas between the baseline and the curve
formed by the moving vector during QJ and JT intervals respectively.
Reprinted from (102). Reproduced with permission from Elsevier.
26
Aims
The aim of this thesis was to improve the diagnostics and risk assessment in
the LQTS by
I: Examining electrocardiographic methods for measurement of the QT
interval
II: Determining the precision of QT measurements in a pediatric population
III: Comparing vectorcardiographic parameters between individuals with
mutations in the KCNQ1 or KCNH2 gene.
IV: Investigating if Swedish carriers of the Y111C mutation compose a
founder population which could be an important source for future studies.
27
Materials
Overview of the LQTS study population in paper I-IV
Subjects
The index cases and family members in paper I-III were recruited from the
LQTS Family Clinic at the Centre for Cardiovascular Genetics at Umeå
University Hospital. The healthy volunteers were recruited from hospital
staff at Umeå University Hospital and their relatives. The healthy volunteers
had to fulfill the following criteria: absence of known heart or lung disease;
no medication affecting the cardiac repolarization; and no history of
unexplained syncope or SCD in any relative younger than 40 years of age.
Genetic testing was performed in index cases and family members, but not in
the healthy volunteers.
The LQTS population (by genetic testing confirmed carrier of LQTS
mutation) was matched for age and sex with a control population (healthy
volunteers and healthy family members’, non-carriers of LQTS mutation) 1:1
(paper I-II).
28
Seventy-five LQT1 individuals (≥ 17 year of age) were matched (age and sex)
1:1; and 3 individuals were matched 1:2 with 78 healthy controls. Five LQT1
children (≤ 16 year of age) were matched 1:1; and 19 were matched 1:2 with
43 healthy children (paper III).
In paper IV, index cases and family members were included from the LQTS
Family Clinic at the Centre for Cardiovascular Genetics at Umeå University
Hospital and also through national referrals to the Department of Clinical
Genetics at Umeå University Hospital.
Subjects in paper I, included from 2005 until 2008
The LQTS population consisted of 94 carriers: 84 LQT1 and 10 LQT2, 16
were index cases and 78 family members. There were 25 adult males: 12
carriers of Y111C, 5 R518X, 6 with other LQT1 mutations and 2 with LQT2
mutations. There were 45 adult females: 16 carriers of Y111C, 18 R518X, 6
with other LQT1 mutations and 5 with LQT2 mutations. There were 24
children of whom 10 were boys: 2 carrying Y111C, 6 R518X, one other LQT1
mutation and one LQT2 mutation; 14 were girls: 5 carrying Y111C, 7 R518X
and 2 with LQT2 mutations.
The control population consisted of 28 family members that were genetically
confirmed non-carriers and 66 healthy volunteers. There were 25 adult
males: 11 non-carriers and 14 healthy volunteers. There were 45 adult
females: 13 non-carriers and 32 healthy volunteers. There were 24 children:
10 boys of which 2 were non-carriers and 8 healthy volunteers; 14 were girls
of which 2 were non-carriers and 12 were healthy volunteers.
Subjects paper in II, included from 2005 until 2009
The pediatric LQTS population consisted of 35 mutation carriers: 29 LQT1
carriers (13 Y111C, 14 R518X and 2 other LQT1 mutations) and 6 LQT2
carriers.
The pediatric control population consisted of 10 family members that were
genetically confirmed non-carriers and 25 healthy volunteers.
Subjects in paper III, included from 2005 until 2011
The LQTS population consisted of 118 carriers: 99 LQT1 and 19 LQT2. There
were 36 adult males: 21 carriers of Y111C, 7 R518X and 8 with LQT2
mutations. There were 58 adult females: 26 carriers of Y111C, 21 R518X and
29
11 with LQT2 mutations. There were 24 children: 10 carriers of Y111C and 14
carriers of R518X.
The control population consisted of 121 individuals. There were 30 adult
males: 16 family members that were genetically confirmed non-carriers and
14 healthy volunteers. There were 48 adult females: 16 family members that
were genetically confirmed non-carriers and 32 healthy volunteers. There
were 43 children: 15 family members that were genetically confirmed noncarriers and 28 healthy volunteers.
Subjects in paper IV, included from 2005 until 2010
The LQTS population consisted of 37 index cases and 21 family members all
carriers of the Y111C mutation in the KCNQ1 gene.
The control population consisted of 84 healthy military recruits, matched for
origin (northern Sweden), corresponding to 168 control chromosomes.
Ethical considerations
All studies were conducted in accordance with the Helsinki Declaration for
Ethical principles for Medical Research Involving Human Subjects (2000).
All studies were approved by the Regional Ethical Review board at Umeå
University (Umeå Sweden) Dnr: 05-127M.
All participants in the study gave written consent including the legal
guardians of the participating children. Information concerning genetic
testing and execution of haplotype analysis was provided to all.
30
Methods
Paper I-III: In all individuals a 12-lead ECG was recorded during rest in a
supine position, and approximately 2 minutes later this was followed by the
recording of a VCG. For VCG recordings, five electrodes were applied around
the chest at the level where the 4th intercostal space meets the sternum, one
in the neck, one on the left hip, and one zero point on the right hip
(according the Frank system) (103, 104). All the recordings were performed
by the same person.
12-lead ECG
Automatic measuring and interpretation of the QT interval
In paper I and II the 12-lead ECGs were recorded with a Mac 5000 version
008B using the equipments 12SL algorithm for automatic calculation and
interpretation of the QT interval (GE Medical System, Information
Technologies, Milwaukee, WI, USA) (105). The paper speed was 50 mm/s,
the amplitude gain 10 mm/mV, and the sampling rate 500 samples per
second. The signal was amplified in a band between 0.31 and 150 Hertz (Hz).
QRS complexes of the same morphology were aligned in time during 10
seconds recording without noises and a representative complex was
generated from the medians obtained at the successive sampling points. The
end of the T-wave was defined on the vector magnitude, which was
calculated from the sum of the absolute value of I, II and V1-V6 and its firstorder difference. The T-wave end was defined as when a new point
contributes to the T area and when that point in the accumulated T area is
below a threshold value (1%). The QT interval was then calculated from the
earliest Q wave in any lead to the T-wave end. According to the equipments
12SL algorithm the QT interval was categorized as normal, borderline, or
prolonged according to the specific criteria of age, sex and heart rate (105)
(Figure 13).
31
Figure 13. Presentation of values and interpretation in 12-lead ECG from
the equipment Mac 5000 version 008B. Calculated parameters: Heart rate
56 BPM, PQ-interval 130 ms, QRS-duration 94 ms, QT/QTc 524/505 ms
and PR-T axis 56, 52 and 39. Interpretation: Slightly slow sinus rhythm
with sinus arrhythmia, prolonged QT-interval, pathological ECG.
Manual measurement of the QT interval
All 12-lead ECGs were coded and, no automatic values or interpretations
were visible for the observers (paper I-II). Four experienced observers
repeated manual measurement of the QT interval in 42 12-lead ECGs on two
occasions with a one week interval between measurements (paper I). All
observers had verbal and written instructions on how to perform the
measurements (Appendices I): the T-wave end was defined according to the
proposal by Goldenberg I et al.(67). The QT interval was corrected for heart
rate according Bazett´s formula. Each observer made a statement based on
cut-off QTc values according to age and gender for diagnosing LQTS (Table
3); normal, borderline (suspected LQTS) or prolonged QT interval (LQTS).
The observer with the lowest intra-observer variability performed the
measurements in the subsequent 146 ECG recordings in paper I and also the
70 ECGs in paper II.
VCG according Frank lead system
Automatic measuring of the QT interval
The CoroNet II system (Ortivus AB, Danderyd, Sweden) was used to
recording all VCGs in paper I, II and III. In paper I the older MIDA1000 was
also used, but there are no relevant differences between the systems. The
orthogonal leads X, Y and Z were recorded in 3-4 minutes, where the signals
were sampled at 500 Hz (amplified band width 0.03-170 Hz). The recording
was performed during period 60 seconds (s) for determination of the
parameters describing the spatial QRS and T vector, T vector loop and QRST
intervals.
32
The average vector magnitude was computed from the X, Y and Z leads
(vector magnitude = √X2+Y2+Z2), the detections points were located in
relation to the Q-point which had the value 0 and the isoelectric line was
located 30 ms before the start of Q. The detection point Q to F corresponded
to the QT interval (Figure 6), and the mean heart rate for one minute was
used in the automatic calculation of the QTc.
The CoroNet II algorithm defines the beginning of QRS and the end of the Twave from the computed derivative of the vector magnitude. In order to find
out the detections points for T end, the algorithm starts from the T peak and
seeks forward until the magnitude decreases with 1/3 of the value of T peak.
The algorithm seeks further forward to a predefined smaller value, and when
the slope of the magnitude crosses that point the algorithm defines this as
the T end. In a similar way the detection point of the QRS start is defined,
from the highest derivative of the QRS complex and backwards until the
magnitude has been decreased to 1/10 or a predefined value. When the
detection point of T end is defined and a U wave is an early part of the Twave, the U-wave was included in the QT interval. If the U-wave comes after
the T-wave, it is not included in the QT interval.
Off-line analysis of the VCG
Paper III: All off-line analyses were performed by one observer. Detection
points were automatically positioned and presented in the vector magnitude
(Figure 6). The last minute of the recording was chosen for analysis; if there
were extrasystolic beats the previous minute were chosen. The end of the Twave was manually assessed by the tangent method (106). Roughly 90 % of
the T-wave end detection points needed manual adjustment. After all
recordings had been reviewed, the data was processed and the VCG
parameters were determined.
Genetic testing
Genomic DNA was prepared from whole blood using the standard salting out
method. Evaluation was performed in order to confirm the presence of
mutation in KCNQ1 and KCNQ2 genes. Amplified Polymerase Chain
Reaction (PCR) fragments were screened for sequence variants by
denaturing high-performance liquid chromatography. In case of variant
elution peaks, further analyses were performed with DNA sequencing
(CEQ8000 sequencer Beckman Coulter, Fullerton, CA). When a mutation
was identified in an index case, the family members subsequently underwent
33
direct analysis using MGB-probes by TaqMan 7000 (Applied Biosystem,
Carlsbad, CA). Based on the molecular diagnosis each subject was classified
as either genotype positive or genotype negative for LQTS (Paper I-IV).
Genealogy, geography and haplotype analysis
Paper IV investigated if the high number of index cases and family members
carrying the Y111C mutation in the KCNQ1 gene constitutes a population
sharing a common haplotype, together with common geographic and
genealogic origin. The age of the mutation and prevalence were also
calculated.
Genealogical and geographic analysis
The genealogic searches were performed by tracing all maternal and paternal
ancestors of 37 index cases, and then connecting as many index cases as
possible in as few generations as possible with a common couple (founder
couple). The maternal or paternal ancestors connecting to the index cases
and the common founder couple were defined as obligate carriers of the
family mutation. All obligate carriers including siblings and spouses were
traced: sex, place of birth and death, were noted if possible. Spouses were
traced to investigate the marriage pattern within or outside the river valley.
The birth places were traced to establish a possible clustering of ancestors
within a geographic area.
According to the population records initiated by the Crown in Sweden in the
year of 1686, the priesthood was obliged to execute annual catechetical
examinations in their local parishes and register the inhabitants by including
births, deaths, marriage and migration. The documentation before 1686 was
often based on e.g., estate inventory proceedings and court proceedings.
These registries give us a unique opportunity to investigate our ancestors.
Genealogical data were collected from church registries, parish books, and
census archives at the Research Archive at Umeå University. Data were also
collected from the Swedish archive information homepage (www.svar.ra.se)
and researcher’s private genealogic database.
All genealogic data were entered and stored in DISGEN computer software
(Lakewood, CO, USA). Open Source software (Inkscape vector graphic
editor) and GIMP (GNU image manipulation program) were used to
construct pedigrees and geographic maps.
34
Below is an example from a church registry of people who died in the parish,
with names and causes of death documented. The individuals in the example
registry have no connection with the LQTS families.
Haplotype analysis
To determine if the index cases and their family members were related and
had the same genetically origin due to founder effect, we examined if they
shared a common haplotype. The haplotype represents alleles inherited
together in related individuals. The closer the microsatellite markers are to
each other, the smaller is the probability of recombination.
We performed haplotype analysis in each index case whenever possible,
including two generations from each family. These analyses were compared
with 84 healthy controls of north Swedish origin.
The point mutation c.332A>G p.Y111C is located in the KCNQ1 gene on the
short arm (p) of chromosome 11 at position 15, where the base A have been
changed to G causing the amino acid to exchange from Tyrosin to Cystein.
We investigated 5-6 microsatellite markers upstream and 9 downstream
from the point mutation. These microsatellites are located over a physical
distance of approximately 8 x 106 base pairs of the chromosome. To work out
the pattern of shared alleles, we reconstructed the most likely ancestral
haplotype. To compare the frequency of disease associated alleles in healthy
non-carriers, analysis of the same microsatellite markers were performed in
168 control chromosomes in 84 healthy controls. We used the National
Centre for Biotechnology Information Entrez Gene database, and the
deCODE, Généthon and Marshfield genetic maps, to choose markers for the
haplotype analysis. The markers with the highest heterogeneity according to
the CEPH Genotype database were selected. For each separate marker
forward and reverse primers flanking the microsatellite region were used
(Sigma-Aldrich Inc.). Fragment analysis was performed according to
manufactory instructions, and the PCR product was analyzed using an
automated capillary electrophoresis–based DNA Sequencer (Wave® 3500
HT, Transgenomic Inc, Omaha, Nebraska). GE Healthcare (United
35
Kingdom) and Applied Biosystems (Foster City, California) supplied
solutions and material for the PCR mix. GeneMapper software version 3.7
(Applied Biosystems Inc, Foster City, California) was used to analyze the
microsatellite data.
Mutation age and prevalence of the Y111C mutation in the KCNQ1 gene
The prevalence and age of a mutation can be investigated by analyzing the
haplotypes in mutation carriers from a common descent. To possibly reduce
the uncertainty in these calculations two different computer programs were
used. The extent of shared alleles in index cases, the frequency of disease
associated alleles in healthy controls, and the recombination frequencies for
the 15 microsatellite markers was computed in the ESTIAGE software (paper
IV). The software estimated the age and determined the 95% confidence
interval (CI). The mutation age was defined as the age of the most recent
common ancestor of the index cases. Recombination frequencies were
estimated using the distance from the Y111C mutation and the markers, and
the standard correspondence 1 cM = 106 base pairs.
The DMLE software (www.dmle.org) was used to estimate the prevalence of
the mutation. Data were entered including the haplotypes of index cases and
controls. The average population growth rate per generation was estimated
based on regional demographic data from the Jämtland and Västernorrland
Counties from the period 1570-1950 in Statistic Sweden (www.scb.se). The
“true value” of the mutation age was assumed when the confidence interval
(CI) of the DMLE and ESTIAGE software overlapped.
Statistic methods
Data were analyzed using SPSS version 16.0 and 18.0 (SPSS Inc. Chicago, IL,
USA) in paper I-III. All values were calculated as mean, range, standard
deviation (SD) and min-max. To assess and identify the efficacy in
diagnosing LQTS for the different electrocardiographic methods (paper I and
II), sensitivity, specificity and positive and negative predictive value (PPV
and NPV, respectively) were computed.
In paper I-II, we compared the electrocardiographic methods by computing
receiver operating curves (ROC), and the area under the curve (AUC) (SAS
version 9.1.3; SAS Institute, Cary, NC). For nonparametric comparison of
AUC, the SAS-macro %ROC version 1.6 was used.
36
Relative error (paper I) and ĸ coefficient were used to assess inter- and intraindividual observer variability and the agreement between the QT
measurements. Relative error was calculated as; absolute error/mean error
of the pair A – B/[(A + B)/2)]. Absolute error was calculated as the error
from two pairs (A, B) from 2 occasions of measuring as the absolute values of
their difference A – B.
Molecular genetic diagnoses were used as gold standard when comparing the
measured QTc between the different methods in paper I and II.
A value of the ĸ coefficient > 0.75 was considered as excellent agreement,
and values < 0.40 was considered poor agreement. p ≤ 0.05 was considered
statistically significant.
Regression analysis was used to investigate the influence of sex, age, KCNQ1
mutation on the VR (paper III). As we found a strong relationship between
age and most VR parameters, we divided the LQTS population into two age
groups: ≤ 16 y (children), and ≥ 17 y (adults), respectively.
We analyzed if healthy volunteers and non-carriers of the family mutation
could be merged to one control group. Linear regression was used to
compare controls and KCNQ1 mutation carriers.
Limitations
Paper I – III: DNA analysis was not performed in healthy volunteers in the
control group. However, the risk for an individual to be carrier of LQTS in
the healthy group is only 1/2000 (0.005%). The generalizability in paper IIII may be limited because the LQTS populations were composed preferably
of KCNQ1 gene mutations and a low number of KCNH2 mutations, but no
SCN5A gene mutations.
The electrocardiographic recordings were performed without consideration
of the diurnal variation or day-to-day variation of the QT interval. More
stringent registration times may possibly have given somewhat different
results. Paper I, II and III: No consideration was taken to beta-blocking
therapy in the analyses of the LQTS population. However, in study III we
showed that in our LQTS population there was only a small change in the QT
interval (16 ms) caused by beta blocking therapy and no changes in the QTc.
37
Paper IV: DNA was available for haplotype analysis in 26 out of 37 index
cases, however, we found that index cases with or without genealogic
connection to the common couple shared alleles to the same extent. This fact
makes it likely that the analyzed index cases sample is representative.
Twenty-six out of 37 index-cases were connected in a pedigree to a common
couple. Some of the reasons why not all could be connected in the pedigree
could be that a child had other parent/s then as stated in the church books,
or because of destroyed church books, or that incorrect data were entered by
the authorities (e.g., the vicar).
38
Summary of Results
Paper I and II





We found a considerable intraindividual and interindividual
variability in the manual measurement of the QT interval in 12-lead
ECG among 4 observers.
The automatic interpretation of the QTc from 12-lead ECG showed
the lowest sensitivity (0.40). It provided 38 out of 94 mutation
carriers of LQTS with a correct diagnosis.
Automatic QTc measurement using VCG showed the highest
sensitivity (0.90) and a positive predictive value (PPV) 0.89 and an
AUC 0.948. It provided 85 out of 94 mutation carriers of LQTS with
a correct diagnosis based on an age and sex limited QTc value.
Also in a pediatric population VCG had the highest accuracy for a
correct diagnosis, 30 of 35 (86%) mutation carriers were correctly
diagnosed as LQTS and 28 of 35 (80 %) non-carriers received the
correct diagnosis.
Automatic measuring with VCG, 12-lead ECG and manually
measuring in 12-lead ECG showed roughly the same specificity 0.870.89. In the pediatric study specificity was nearly equal in the four
methods.
Paper III




In adult men and women ≥17 years of age:
A significant longer QT interval (p=0.037) was found in the
symptomatic group when comparing 23 symptomatic and 52
asymptomatic KCNQ1 mutation carriers.
There was a significant difference (p=0.02) in QTc between the
populations carrying Y111C and R518X mutation in the KCNQ1 gene,
where the Y111C population had a longer QTc.
There were a significant difference between the LQT1 population
and the control population were the LQT1 population had longer
QTc (p=0.000) and longer Tp-e interval (p=0.000).
The QTc and Tp-e/QT was longer in LQT2 carriers and the Tarea and
Tamplitude were greater in LQT1 carriers, but all within a normal range.
39

In children 1-16 years of age:
There were a significant difference between the LQT1 population
and the control population, were the LQT1 population had longer QT
interval (p=0.009) and longer QTc (p=0.000), while the Tp-e/QT
ratio was larger in the control population (p=0.000).
Paper IV
The Y111C population being a founder mutation is supported by:
 Genealogic studies connected 26 of 37 living carriers of the Y111c
mutation in the KCNQ1 gene through a line of obligate mutation
carriers to a common founder couple born 1605 resp. 1614 (Figure
15).
 Geographic clustering back to a common geographic origin in the
region of the Ångerman river valley and their tributaries were traced
in ancestors to all 37 index cases (Figure 16).
 Haplotype analysis traced an original ancestral haploblock in the
DNA in 26 index cases and 21 family members.
 The age of the mutation was calculated to 600 years (CI 450; 850)
and 575 years (95% CI 400; 900) with the ESTIAGE and DMLE
software, respectively.
 A prevalence of 1:1,500 – 3,000 carriers was calculated for the Y111C
mutation in the KCNQ1 gene in the counties of Jämtland,
Västernorrland and Västerbotten.
40
Figure 15 Twenty-six index cases carrying the Y111C mutation in the
KCNQ1 gene connected through obligate carriers of the mutation to a
common couple born in 1605 and 1614 spanning 13 generations. =Index
cases; H=Index cases with haplotype data. Reprinted from (107).
Reproduced with permission from Elsevier.
41
Figure 16. Birthplaces of the 37 index cases and their ancestors, all carriers
of the Y111C mutation in the KCNQ1 gene. Birthplaces in the 19th century are
depicted in a map illustrating the geographic clustering of the mutation (grey
shaded area). Depicted lines illustrate the rivers and tributaries that flow
from northwest to southeast and the dots indicate the birthplace of the
ancestors. The grey shaded geographic area of interest is magnified in the
upper left corner. Reprinted from (107). Reproduced with permission from
Elsevier.
42
Discussion
Manual measurements
Long QT is a widespread and potentially lethal disease because of the risk of
the feared arrhythmia - known as TdP. The warning sign could be a noticed
long QT interval, but it has been shown that many physicians, including
many cardiologists, do not recognize a prolonged QT interval (108). This
may be due to the difficulty in defining the end of the T-wave and/or a lack
of experience in performing the measurements, which produces a significant
intra- and inter-variability in the measurements of the QT interval. It is of
utter importance to accurately measure and identify a long QT interval - both
for the individual that is at risk of arrhythmia and for those without risk. In
children, manual measurements of the QT interval are even more difficult
due to high and variable heart rate (sinus arrhythmia).
In accordance with other studies (1, 108), we found (paper I) considerable
problems with the manual method for measuring QT intervals. In a study by
Postema et al., 151 students with no experience in manual measurement of
the QT interval were taught to measure the QT interval by the tangent
method (Figure 5). They measured and calculated QTc and interpreted four
ECG (two normal and two LQTS) on two occasions and their results were
compared with those of arrhythmia experts, cardiologists and noncardiologists (109). The students achieved a correct classification rate of 71%
and 77% on the first and second occasion, compared with 62% for the
arrhythmia experts and less than 25% for the cardiologists and noncardiologists. As a consequence the authors proposed that the tangent
method should be used to achieve a better stratification for individuals that
are at risk for sudden cardiac death (SCD).
The tangent method is reliable and easy to learn and has acceptable
variability. However, the tangent method does not account for the entire QT
interval and is problematic in T-waves with low amplitude (110), which may
have implications for diagnosis and risk stratification. In paper I and II we
used the method, as proposed by Goldenberg et al., since it includes the
whole end of the T-wave and thereby the entire QT interval. The tangent
method was used in the VCG off-line analysis (paper III), which makes study
III comparable with other studies performed with the same VCG equipment
(93, 102, 111-114).
In VCG recordings, the automatically measured QTc were compared with
QTc manually measured, using the tangent method (unpublished results).
43
The study population consisted of both adults and children including 105
individuals with DNA verified LQTS and 118 healthy controls. In accordance
with other studies we found that the mean QTc in all individuals was
significant shorter, with the tangent method (427±35 ms) compared with the
VCG method, (445 ±35 ms, p<0.0001) (Table 4) (69).
Table 4. QTc measured automatically with the VCG equipment and
measured manually using the tangent method in the same recordings
(unpublished results)
Mean± SD;CI Mean± SD;CI
Mean± SD;CI
All
Control
LQTS
n=223
population n=118 population
n=105
VCG QTc ms,
445±35
421±19
472±31
automatically
440;450
418;425
465; 476
VCG QTc ms,
427±35
404±21
454±29
manually tangent
423;432
400;407
447; 458
QTc: Heart rate corrected QT interval (Bazett`s formula); SD: Standard
deviation; CI: Confidence interval; Control population: DNA confirmed noncarriers of a LQTS mutation and healthy volunteers; LQTS population: DNA
confirmed carriers of a LQTS mutation; ms: milliseconds; VCG
vectorcardiogram
Automatic methods
To overcome the intra– and inter-individual variability in manual
measurements of the QT interval, a reliable automatic method would be
valuable. But in paper I and II, we showed that automatic ECG interpretation
may lead to an erroneous diagnosis. A study of 97 046 ECGs analyzed by the
Marquette 12 SL ECG Analysis Program (GE Healthcare), a system that also
was used in this thesis, showed a manifest underreporting of prolonged QT.
Out of 16 235 (16.7%) ECGs with prolonged QTc only 7709 (47.5%) were
stated as “prolonged QT” (115).
We showed in paper I a higher accuracy in automatic QTc measurement by
VCG. The VCG recordings with electrodes applied according to the Frank
lead system (Figure 7) and the algorithm that performed the automatic
measurements of the QT interval provided the best combination of
sensitivity and specificity (AUC 0.948).
44
The higher accuracy in automatic QTc measurement by VCG may be
explained by that the vector magnitude is calculated from three orthogonal
leads and that there are electrodes that cover the posterior parts of the heart
(Z lead).
When investigating a pediatric population of LQTS mutation carriers and
healthy controls we found that, based on QTc and a QTc limit of 440 ms,
VCG identified 30/35 (86%) of the carriers. VCG incorrectly diagnosed five
children as having LQTS. The automatic interpretation of the 12-lead ECG
identified only 17/35 (49%) of the carriers. One reason to VCGs superiority
and high precision in measurements of QT interval in a pediatric population
could be that the VCG recording is longer compared to a standard ECG
recording. The sampling time for the heart rate was 60 seconds for the VCG
and 10 seconds for 12-lead ECG. This may have influenced the QTc,
especially in a pediatric population with varying heart rate. When comparing
the calculated mean heart rate between VCG and 12-lead ECG in 70 children,
the mean heart rate was nearly the same. But, when analyzing each
individual’s heart rate, calculated with both methods, we found that in 14 out
of 70 children (20 %) the heart rate differed ≥10 bpm (max 22 bpm) between
VCG and 12-lead ECG (unpublished data).
QTc cut-off values
There are carriers of LQTS mutations with normal QTc, and there are
healthy individuals with prolonged QTc interval, as has been shown in
earlier studies (73, 76). It is thus not possible to define a QTc value adjusted
for age and sex that can sort out all carriers of a LQTS mutation from healthy
individuals.
The distribution and different cut-off values of QTc were examined in 81
adult carriers (50 women) and 82 non-carriers (52 women) (unpublished
results). Applying QTc cut-offs 430, 440 or 450 ms in the control population
would state 24%, 12% and 2%, as having prolonged QT interval. If the same
cut-off limits were used in the LQTS population, 96%, 90% and 80% would
have prolonged QT interval. Table 5 show the percentages calculated for
both populations. In Figure 14, individual QTc values are plotted against
age for controls and carriers of a LQTS mutation, where lines mark the
different investigated cut-off limits for prolonged QTc.
Over time there is a significant variability in the duration of the QTc. At
baseline 25 % of 375 LQTS children had QTc ≥500 ms while 40 % during the
45
following 10 years at some point had QTc ≥500 ms (42). This highlights the
importance of performing repeated ECG measurements of the QTc for the
diagnosis of LQTS, and to investigate the clinical and family history before
deciding to perform genetic testing (73).
Table 5. The effect of different QTc cutoff values on the statement prolonged QT.
QTc cut-off
Statement
prolonged
QT
430 ms
440 ms
450 ms
Control
Population
All
n=82
20
(24%)
10
(12%)
2
(2%)
Female
n=52
9
(17%)
2
(4%)
LQTS
Population
Male
n=30
3
(10%)
1
(3%)
All
n=81
78
(96%)
73
(90%)
65
(80%)
Female
n=50
47
(94%)
45
(90%)
Male
n=31
28
(90%)
26
(84%)
QTc: Corrected QT interval (Bazett formula); Control population:
Healthy family members and healthy volunteers; LQTS population:
Genetically confirmed carriers of a LQTS mutation.
Figure 14. QTc automatically measured with VCG against age for controls
(left) and the LQTS study population (right). Lines show different QTc limits.
46
QTc cut-off levels for LQTS diagnosis were set to 430 ms, 440 and 450 ms
for males, children and females respectively (paper I and II). These values
correspond to the lower limit of borderline QTc, as proposed by Goldenberg
et al. (67) (Table 3). These QTc limits should not be considered as absolute
limits for a LQTS diagnosis, but as a wake up bell raising the question - could
this be a LQTS patient?
The “ideal” QT measurement
The ideal ECG equipment would give us an accurate QT measurement
without the manual procedure's problems. It has previously been shown that
automated QT measurement provides considerable less variability (116).
Modern ECG equipment provides digital on-line recordings with automatic
measurements and interpretation of the ECG. It is however still important
that the ECG is examined by an experienced person.
A standardized algorithm and a uniform definition of recording
circumstances would improve the diagnostic of diseases that alter the QT
interval. It would also improve the possibilities to compare values from
different studies. This is difficult today where several different methods are
in use for QT measuring and often, also in high-impact LQTS studies,
without accounting of how the QT intervals were measured (method, lead,
etc.). ECG recordings are performed in various settings by staff with varying
educations. To maintain the quality and the clinical value it is important to
have well educated paramedical staff that correctly perform the ECG
recordings, knowing the importance of: correctly placed electrodes,
especially the precordial leads, in relation to body surface anatomical
landmarks, connecting the correct electrode cable to the correct electrode,
and assuring that there is minimal interference from skeletal muscles and
artifacts from skin-electrodes or implanted or external electrical or electronic
devices that otherwise hampers the use of the recordings.
Electrophysiological phenotype
The clinical risk stratification in LQTS is based on LQTS type, age, sex,
symptoms, family history and QTc duration (41). Within a family and
between families affected by the same LQTS type and even the same
mutation QTc can vary considerably. We have shown in paper I and II that
VCG accurately estimates QT interval as compared with 12-lead ECG (96,
47
117). VCG may be more sensitive to changes in VR and provide more
information than just the duration of the QT interval (101). Therefore, VCG
may be a valuable contribution in the assessment of increased VR dispersion.
The Y111C and R518X mutations in the KCNQ1 gene have different effects on
the IKs ion channel function (118). R518X is a nonsense mutation causing a
≤50% reduction of the channel function (haplo-insufficiency). The Y111C
mutation is a point mutation with a dominant negative effect with >50%
reduction of channel function (>75% has been shown in vitro) (119).
The electrophysiological phenotypes (e.g., VG, Tarea, and Tazimut) of the two
mutations were examined with VCG. The findings were compared with a
healthy control population and a population of mutation carriers in the
KCNH2 gene. Data analyses showed that age, sex and carriership of a LQTS
mutation affected most VR parameters; consequently, the population was
divided into adult men, adult women (≥17 years of age), and children 1-16
years of age. All recordings were performed during rest with the individuals
in supine position, which might explain why we did not find signs of
increased dispersion in the ventricular repolarization except for a longer QTc
in the LQTS populations. We have earlier found that carriers of the Y111C
mutation in Sweden has a low incidence of life threatening cardiac events
despite the severe functional defects shown in in vitro studies (120).
Is this a sign of modifying factors? Could unknown mechanisms compensate
the impaired channel function by physiological redundancy expressed as
retained repolarization reserve?
A more prolonged QTc and a higher number of cardiac events have been
found in LQTS populations with dominant negative effect compared with
haplo-insufficiency (119). The clinical phenotype is linked to the mutation
and its biophysical effects on the cell membrane. It has been shown that the
localization of the mutation has importance, a first cardiac event were seen
more often in missense mutations and mutations located in the transmembrane part of the protein rather than C-terminally located mutations
(119).
48
Ventricular repolarization
In healthy individuals it has been shown that the VR duration shortens and
the QRSarea, Tarea and Tamplitude decreases with increased heart rate (113). The
conclusion was that an increased heart rate in healthy individuals decreases
the ventricular depolarization instant, AP morphology and thereby the global
VR. We found no significant difference in heart rate and no significant
changes in VG, Tarea and QRSarea in paper III.
Increased autonomous nervous activity can also be critical in LQTS if the
repolarization duration does not shorten appropriately during sympathetic
stimulation. Pharmacologic perturbations of autonomic nervous system
(ANS) and the response of VR parameters recorded by VCG have been
studied in healthy individuals (102). β-adrenergic stimulation after
muscarinic blockade (atropine) gave a transient prolonged QT interval and
delayed heart rate adaption of Tarea and VG, thus mimicking pathological
conditions with increased risk of arrhythmia such as LQTS. In Y111 carriers
syncope was most commonly seen in association to physical activity or
emotional stress (120), as also has been shown to be a trigger in other
KCNQ1 mutations.
Risk markers
LQTS is a genetic heterogenic inherited disease with variable penetrance
(30-50% of the carriers never have symptoms) and expressivity. More
knowledge of the association link between genotype and phenotype is
needed. The degree of QT interval prolongation is a known risk marker for
syncope and/or cardiac arrest in LQTS. Despite that, syncope and/or cardiac
arrest happens in 5% of LQTS mutation carriers with a normal QT interval
(121).
Other diagnostic parameters and risk markers than QTc have been evaluated
in different LQTS populations. Increased short-term variability of the QT
interval in drug-induced LQTS and AP instability were useful in the
predicting arrhythmia (122, 123), and may be used as an additive noninvasive diagnostic marker in LQTS (124). We previously performed a beat to
beat analysis of the QT interval and found that most VR parameters during
resting conditions showed a significant larger instability (by a factor of 2) in
carriers of a KCNQ1 or KCNH2 mutation compared with a control
population (114). The beat to beat instability of the QT interval increased
with increasing QT interval, also seen as increased VR dispersion measures -
49
Tarea (global dispersion) and VG (action potential morphology dispersion).
This may be a marker of VR variability with valuable clinical implications,
but this has to be confirmed in further studies with additional clinical
(phenotype) and genetically (genotype) data (125). It would be valuable to
perform such studies in populations with a high number of individuals with
the same mutation.
Founder population Y111C
Founder populations are of special interest because they give, in a genetic
homogenous population, a possibility to investigate the relation between
genotype, phenotype and modifying factors.
With our genealogical, geographical, epidemiological, and haplotype data we
have identified a founder population in the area around the Ångerman river
valley consisting of carriers of an Y111c mutation in the KCNQ1 gene. The
mutation was estimated to date back to the 15th century. The immigrants to
the inland of the northern river valleys lived relatively isolated from other
river valleys, the geographic isolation created condition for the occurrences
of founding of genetic sub-isolates. We investigated the marriage-pattern of
the obligate carriers in the pedigree and found that the spouses under the
17th and 18th centuries were born in the Ångerman river valley. Other LQTS
founder mutations have been described, e.g., the A341V founder mutation in
the KCNQ1 gene in South Africa (126), for which in vitro studies found it to
be functional mild although the clinical phenotype is severe. These findings
have given valuable contributions to the understanding of risk modifiers in
LQTS.
When we started the LQTS Clinic at the Centre for Cardiovascular Genetics
at Umeå University Hospital we found a high number of families (unaware of
each other) carrying the Y111C mutation in the KCNQ1 gene. We have earlier
described the mutation to have a mild clinical phenotype with a low 0.005%
annual incident of life- threatening events (120). The mild phenotype
enabled the enrichment in the isolated river valley and has contributed to the
high number of today living carriers of the Y111C mutation (> 200 carriers
2013).
These findings do not correspond with the severe in vitro
electrophysiological characteristic of the mutation which has >75%
mutation-associated reduction of Ks channel function (118, 127).
Consequently, there must be other unknown factors affecting the clinical
50
phenotype. This large founder population is a valuable basis for future
studies of phenotype and genotype correlations and modifying factors that
affect the disease.
Conclusion
VCG was found to be an accurate method for the initial diagnosis of LQTS.
QT interval measurements performed with vectorcardiography have high
precision in a pediatric population.
Ventricular repolarization analysis by resting VCG showed a significant
difference in QTc between Y111C and R518X mutations in the KCNQ1 gene.
VCG showed no increased ventricular repolarization dispersion in KCNQ1
and KCNH2 mutation carriers.
We have identified the first Swedish LQTS founder population carrier of the
Y111C mutation in the KCNQ1 gene. This founder population will be an
important source to future LQTS research in diagnostics methods and the
correlation of phenotype, genotype and modifying factors.
51
Acknowledgements
My first thanks and tokens of appreciation must be directed to Steen M
Jensen, my principal supervisor and workmate through many years. I thank
you for the faith and support you have awarded me and the help that has
attended me throughout the process resulting in the completion of this
thesis. You have freely shared your friendship and your cardiological
insights.
Next I want to express my great gratitude to my co-supervisor Annika
Rydberg. You are always there when you are needed with your
encouragement, boosting my self-confidence and sharing your generous
friendship and knowledge.
Thanks to my co-authors and the members of our LQTS research group of
which Steen M Jensen and Annika Rydberg are part and also:
Annika Winbo, You are a whirlwind! Thank you for the inspiring
conversations and the fruitful collaboration.
Eva-Lena Stattin, I thank you for sharing your insights in genetics, always
willing and able to give good advice.
Lennart Bergfeldt, the Sahlgrenska Academy at the university of
Gothenburg, my co-author in paper III, thank you for your amiability, good
advice, and your liberality in sharing your vast knowledge.
Farzad Vahedi, the Sahlgrenska Academy, University of Gothenburg, my
co-author in paper III, thank you for en enriching collaboration and your
hospitality at my visit in Gothenburg.
Milos Kesek, co-author in my first work – thank you for sharing your
knowledge.
Johan Persson, statistician and co-author of paper IV – thank you for the
analysis of the “statistics of the founder effect”.
Further, I would also like to thank:
Marcus Karlsson for all the invaluable help and all the good advice you
have been giving me through the years.
52
Urban Wiklund always willing to help, thank you so much.
Ina, Mona, Barbro and Anita, you are fantastic – thank you for all the
amusing family receptions.
Stefan Escher for introducing me into the world of genealogy.
Mats Danielsson and the staff at the Research Archive at the University of
Umeå, for all the good advice and aid in my genealogical research, and the
interpretations of “fuzzy handwritings” in the church registers.
Rolf Hörnsten for your support and for finding the right ECG–strips.
Urban Hellman, thank you for the inspiring conversations in “genetics”.
Katarina Englund, my colleague and friend at the Center of
Cardiovascular Genetics, for your existence, for always being there during
my absence and splendidly running our daily work.
Ulf Näslund, Stellan Mörner, Kerstin Franzen thank you for
providing time, your support and working conditions.
Kerstin Rosenquist for the administrative service during the making of
this thesis.
The staff at Clinical Physiology, Clinical Genetics and Center of
Cardiovascular Genetics, thank you for all the help and support you’ve
given me towards the completion of this thesis.
My family – my children and their families especial John, and first and
last you, Thomas – thank you for all the happiness, the love and the
support.
There are many people as have stood me by in the making of this thesis, not
mentioned in these acknowledgments. I send you all my thanks and my
appreciation.
This thesis was supported by grants from the Swedish Heart-Lung
foundation and Northern County Councils Cooperation
Committee.
53
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67
Appendices
I Instructions in manual measurement of the QT interval, translated.
II Long QT syndrome Questionnaire, translated.
1
I - Instructions in manual measurement of the QT interval (translated)
Manual measurement of the QT interval
Measure 3 QT interval in lead II, V5 and V6, the interval should be specified
in milliseconds (ms). Use a ruler or sender, whatever you normally use.
Measure 3 RR-intervals in lead II, specify the interval in ms.
Mark clearly on the ECG the measuring points and write down the value
under the ECG complex.
Each ECG has a code - 1, 2, 3 and so on - in the attached table. Enter your
measurements from ECG coded 1 into code 1 in the table and so on. Leave
the box or boxes empty if you have no value to enter.
At the end of each row in the table there are 3 options for the assessment of
measured QTc. The 3 options are normal, borderline and prolonged QTc
according to the table below. On each recorded ECG you can read age and
sex on the individual. Cross mark the corresponding box for your
assessment.
Children 1-15
Adult male
Adult female
year (ms)
(ms)
(ms)
Normal
<440
<430
<450
Borderline
440-460
430-450
450-470
Prolonged
>460
>450
>470
It is well known that the T-wave end is difficult to assess because of low
amplitudes, biphasic T-waves, discerning which is-U wave and which is Twave. These are among the issues often mentioned that render the
assessment problematic. You are one of four observers in a group where the
measurements of the QT intervals are compared. Two observers are
classified as habituated to measure the QT interval and two as less habit.
QT interval values, recorded and automatically measured by two different
ECG equipments will be compared with each observer’s QT interval values. If
you have any questions during the course of your work please contact any of
the following. Thank you for participating in this work!
Ulla-Britt Diamant phone: 52729 or Steen Jensen phone: 51760.
2
II - Long QT syndrome questionnaire (translated)
Patient questionnaire
Patient information: name birth year, index relative with the disease
1.
Have you had symptoms of the disease Long QT Syndrome that
occurs in your family? (for example dizziness, loss of consciousness,
convulsions) Yes/No
If Yes, describe your symptoms.
If No, go to question 5.
2.
3.
4.
5.
In which situations have you experienced the symptoms described?
How old were you at symptoms debut?
When did you experience you most recent symptom?
Have you had contact with the health care system in relation to
syncope, loss of consciousness or convulsions? Yes/No
If Yes, when, and at which hospital?
6. Do you have normal hearing? Yes/No
If No, have you consulted an Auditory Clinic? At which hospital?
7.
Do you have any additional diseases for which you attend controls
and/or are receiving treatment for? Yes/No
If Yes, what diseases and/treatments?
8. Have you been diagnosed with Long QT Syndrome?
If Yes, when?
9. Have you been prescribed/recommended medical therapy? Yes/No
If Yes, what medicine and in which dosage?
10. Are you currently taking the medication? Yes/No
3
If Yes, since when are you taking the medication? Are you taking the
prescribed dosage?
If No, why are you not taking the medication?
11. When taking the medication, do you experience any adverse effects?
Yes/No
If Yes, describe the adverse effects.
12. Is there anything you like to add with regards to the disease,
symptoms, controls, medication or other aspects?
4