Disease Causing Genes

Prematurity ere'

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List of Papers

I J Klar, B Åsling, B Carlsson, M Ulvsbäck, A Dellsén, C Ström, A Forslund, G Annerén, JF Ludvigsson, N Dahl

RAR-related orphan receptor A isoform 1 (RORa1) is disrupted by a balanced translocation t(4;15)(q22.3;q21.3) associated with severe obesity. Submitted European Journal of Human Genetics

II J Klar, T Gedde-Dahl Jr, M Larsson, M Pigg, B Carlsson, D Tentler, A Vahlquist, N Dahl

Assignment of the locus for ichthyosis prematurity syndrome to chromosome 9q33.3–34.13 J. Med. Genet. 2004;41:208-212

III M Larsson, J Klar, T Gedde-Dahl Jr , M Pigg, A Vahlquist, N Dahl The locus for ichthyosis prematurity syndrome is restricted to 231 kb on chromosome 9q34.11. Manuscript

IV J Klar, C Frykholm, U Friberg and N Dahl A Meniere’s disease gene maps to a 463 kb region on chromo-some 12p12.3. Manuscript

Contents

Introduction...................................................................................................11Heredity and Human Disease ...................................................................11

The Molecule of Heredity....................................................................11Organisation of the Genome................................................................12Human Genetic Variation and Disease................................................13

Identifying Human Disease Genes ...........................................................13Positional Cloning ...............................................................................13Chromosomal Abnormalities...............................................................14Genetic Linkage...................................................................................17

Present Investigations ...................................................................................22

Aims..............................................................................................................23Obesity .....................................................................................................23Ichthyosis Prematurity Syndrome (IPS)...................................................23Meniere’s Disease (MD) ..........................................................................23

Obesity ..........................................................................................................24Introduction ..............................................................................................24Subjects ....................................................................................................24Hypothesis................................................................................................25Results ......................................................................................................25

Paper I..................................................................................................25

Ichthyosis Prematurity Syndrome (IPS) .......................................................27Introduction ..............................................................................................27Subjects ....................................................................................................28Hypothesis................................................................................................28Results ......................................................................................................28

Paper II ................................................................................................28Paper III ...............................................................................................30

Meniere’s Disease (MD)...............................................................................33Introduction ..............................................................................................33Subjects ....................................................................................................34Hypothesis................................................................................................34Results ......................................................................................................34

Paper IV...............................................................................................34

Discussion.....................................................................................................36

Acknowledgements.......................................................................................38

References.....................................................................................................40

Abbreviations

aa Amino acid ARCI Autosomal recessive congenital ichthyosis bp Base pair cM centi-Morgan BCE Before the common era DNA Deoxyribonucleic acid FISH Fluorescence in situ hybridisation FMD Familial Meniere’s disease IPS Ichthyosis prematurity syndrome LD Linkage disequilibrium LOD Logarithm of odds ratio Mb Mega-base pair MD Meniere’s disease PEV Position effect variegation RNA Ribonucleic acid SNP Single nucleotide polymorphism SMD Sporadic Meniere’s disease STR Short tandem repeat

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Introduction

Heredity and Human Disease The Molecule of Heredity The first idea of hereditary traits in humans was proposed as early as 400 BCE by Hippocrates1. He theorized that the male’s contribution to the child’s hereditary traits is transferred to the mother via semen, and that the mother equally contributes with similar reproductive material. Hippocrates called the reproductive material gonos, meaning “seed”, a term that later became the basis of the word “gene” [1]. He also believed that diseases could be inherited and describes that the origin of epilepsy lies in heredity and is transmitted by this seed [2].

In the 1860s, Friedrich Miescher2 isolated from white blood cells a white slightly acidic substance of unknown function which he called “nuclein”. This substance will later be known as deoxyribonucleic acid, or DNA. At the same time Gregor Mendel3 and Charles Darwin4 were publishing their theo-ries of genetics and evolution, but no one suspected that a simple molecule such as DNA was the key to our heredity [3, 4]. Scientists knew that there were molecules in the nucleus responsible for heredity, but since DNA con-sisted of only four different nitrogenous bases; adenine (A), cytosine (C), guanine (G) and thymine (T), deoxyribose sugar and a phosphate group as building blocks, proteins which are made from a combination of 20 different amino acids where much more likely candidate molecules.

In 1928, Frederick Griffith5 identified a transforming factor that was ca-pable of transmitting infectiousness between different bacteria. The infec-tious trait of the bacterium was also inherited when it divided. He could also show that it was the DNA in the bacteria that was the transforming factor, not the proteins [5]. But it was in 1950 Alfred Hershey and Martha Chase6

performed experiments demonstrating that only the DNA is inherited from one generation to the next, thus, is the hereditary material [6]. It was thereby

1 Hippocrates – Greek physician 460 – 377 BCE. The father of modern medicine. 2 Friedrich Miescher 1844 – 1895. 3 Gregor Mendel 1822 – 1884. The father of genetics. 4 Charles Darwin 1809 – 1882. The father of evolutionary theory. 5 Frederick Griffith 1881 – 1941. In what is today known as Griffith's experiment, he discov-ered the transforming principle, which is today known as DNA. 6 Alfred Hershey 1908-1997 and his assistant Martha Chase 1923-2003 conducted the Her-shey-Chase experiment showing that DNA, not the proteins, contains the genes.

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shown that DNA is actually the reproductive material containing the genes Hippocrates talked about 2350 years earlier.

In 1953 Watson and Crick7 elucidated the structure of the DNA molecule to be a double helix [7], subsequently Crick introduced the central dogma of genetics, that DNA makes RNA makes protein [8]. The genetic instructions of the DNA are stored in the genes; a gene is the entire DNA sequence re-quired for synthesis of a functional protein or RNA molecule. The instruc-tion stored in the DNA is copied into RNA in a process called transcription.The RNA is then used as a template to translate it into proteins.

Organisation of the Genome The DNA contained in an organism is called the genome. The ability to ac-cess the genetic information encoded in the genome is dependent on how the cells store, retrieve, and translate this information. For the genes to be read-ily accessed the DNA is bundled into chromosomes. The human genome is diploid, which means we have two sets of chromosomes, one set inherited from each parent. In humans, each parental chromosome set consists of 22 autosomes (non-sex chromosome pairs) and one sex chromosome. In total the human genome consist of 46 chromosomes of which two are the sex chromosome pair. The chromosome constitution is summarised by the karyotype that states the total number of chromosomes and the sex chromo-some constitution. The karyotype for humans is 46,XX and 46,XY for fe-males and males respectively.

KaryotypingThe chromosome consists of euchromatin regions, which contain active DNA and heterochromatin region, which contain inactive DNA. The discov-ery that different chromosomes could be organised and analysed under a microscope is called karyotyping. This is performed by a staining technique called chromosome banding. Chromosome banding is based on the fact that different parts of the chromosome have different ratios of each of the four base nucleotides, A, C, T and G. Since regions rich in GC are more common in euchromatin than in heterochromatin, these regions can be labelled prefer-entially. The first technique was invented by Lore Zech and Torbjörn Cas-persen8 who used a chemical, acridine quinacrine mustard, which has an affinity for the G base of DNA to band chromosomes [9]. Stained with this chemical the chromosomes showed a bright and dim banding pattern when placed under fluorescent light. This banding technique called Q-banding

7 James Watson and Francis Crick – For their discoveries concerning the molecular structure of nucleic acids and its significance for information transfer in living material, they were awarded the Nobel Prize in Physiology or Medicine in 1962. 8 Dr Lore Zech and Dr Torbjörn O Caspersson invented the process of identifying individual chromosomes.

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allowed the identification of all the individual chromosomes in the human genome [10]. Several patterning protocols followed of which G-banding (Giemsa-banding after trypsin treatment) became the most prominent in human cytogenetics for karyotype analysis and chromosome identification [11].

Human Genetic Variation and Disease The genetic constitution of an individual is called a genotype. The relation-ship between the genotype we inherit and the traits, or phenotype, that we manifest is dependent on both genetic variations and environmental factors. On average, any two people taken at random differ only in 0.1% of their DNA sequence or in about one in every 1000 nucleotide pairs in. The ge-netic differences in the human genome occur due to spontaneous changes, mutations, in the DNA sequence. Common sequence variations that occur in a human population with a frequency of more than 0.01 are called DNApolymorphisms. The small differences that do exist are important in the con-tribution to the genetic diversity of the human species, but some of these small differences also involve many medically important variations includ-ing susceptibility to disease [12].

Identifying Human Disease Genes

“All human disease is genetic in origin”

This controversial statement made by Paul Berg9 is an exaggeration, but only a slight one. It has been increasingly evident that most human diseases are rooted in our genes and all we have to do now is to find those genes as re-plied by James Watson7 [13].

Positional Cloning Positional cloning has been a widely used method to identify genetic causes of human diseases. Positional cloning is the identification of a gene depend-ent on knowledge only of the subchromosomal location of the gene [14-16]. The goal is to define a candidate region as closely as possible and the two most commonly used tools are chromosomal abnormalities and genetic link-age analysis.

9 Paul Berg – For his fundamental studies of the biochemistry of nucleic acids, with particular regard to recombinant DNA, he was awarded the Nobel Prize in Chemistry in 1980.

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A History of Positional Cloning The gene for Duchenne muscular dystrophy (DMD) was one of the first genes to be cloned by 'reverse genetics', later more appropriately termed 'positional cloning'. In 1982 the loci for DMD was mapped to Xp21 byrestriction fragment length polymorphisms, but it was in fact the discovery of rare affected females that lead to the identification of the gene. At this time about 20 affected females carrying X; autosome chromosomal translo-cations had been identified and all carried one breakpoint at Xp21. It was the cloning of such a translocation breakpoint that in the end lead to the identifi-cation of the gene, thereby successfully using both positional cloning by linkage analysis and the study of chromosomal translocations to iden-tify a disease causing gene. This represents a starting point in the identifi-cation of genes for disorders based only on positional information. The iden-tification of the genes for chronic granulomatous disease, Huntington dis-ease, retinoblastoma and cystic fibrosis followed soon after.

Chromosomal Abnormalities In the process of identifying genes for genetic disorders one can take advan-tage of chromosomal abnormalities. The hypothesis is if a chromosomal rearrangement is detected in the karyotype of a patient it could be associated with the disease. Gene or genes can be affected by the rearrangement and by characterising the rearranged region one can pinpoint the candidate region of the disorder. There are two major types of chromosomal abnormalities, nu-merical and structural abnormalities.

Numerical Abnormalities The numerical abnormalities involve the change of the number of chromo-somes, without chromosome breakage. An individual may miss either a chromosome from a pair (monosomy) or has more than two chromosomes of a pair (trisomy). Multiple numerical abnormalities are common in malignant cells [17].

Structural Abnormalities Structural abnormalities involving human chromosomes are estimated to

occur in 1% of newborn infants [18]. Structural abnormalities alter the chromosome structure and are due to chromosome breakage. This can result in balanced or unbalanced chromosome abnormalities, with a loss or gain of material, or without loss or gain of material, respectively. Different types of structural abnormalities may occur depending on the number and the local-isation of chromosome breakpoints. When a chromosome breaks at one point only, the two ends at the breakpoints are normally rejoined by repair en-zymes. However sometimes the acentric chromosome fragment can be lost

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leading to a terminal deletion. This is due to the loss of the telomere on one end which usually results in an unstable and degraded chromosome. If two breaks occur on a single chromosome this can result in three chromosome abnormalities, (i) inversions; when portion of the chromosome has broken off, turned upside down and reattached, therefore the genetic material is inverted, (ii) interstitial deletions; where a portion of the chromosome is missing or deleted, or a (iii) ring chromosome; where a portion of a chromo-some has broken off and formed a circle or ring [17].

Chromosomal Translocations If breaks occur on more than one chromosome derivative chromosomes may be formed. This happens when a portion of one chromosome is transferred to another in an event known as chromosomal translocation. There are three main types of translocations, reciprocal, centric, and insertional transloca-tion. (i) In a reciprocal translocation, segments from two different chromo-somes have been exchanged (Figure 1), (ii) in a centric or Robertsonian translocation, an entire chromosome has attached to another chromosome at the centromere, and (iii) an insertional translocation occurs from three chro-mosome breaks where the insertion of the chromosome segment located between two breakpoints is inserted into an interstitial site. This can occur on the same or on a second chromosome and can result in partial monosomy or partial trisomy [17].

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Figure 1. A reciprocal translocation. Segments from chromosome 4 and 20 have been exchanged to form derivative chromosomes. Adapted from “Talking Glossary of Genetics”.

Positional Effect Chromosomal breakpoints do not need to directly disrupt a gene to cause a disease, but can also alter gene expression by positional effect. Several hy-potheses have been proposed to explain this phenomenon. (i) The chromo-somal translocation could separate the gene or promoter elements from es-sential distant regulatory elements. (ii) The rearrangement may juxtapose the gene with enhancer elements from another gene and thereby modifying the expression. (iii) The translocation could position the gene and the regulatory elements close to a different gene and cause competition between the genes for the regulatory elements. (iv) The rearrangement could give rise to posi-tion effect variegation (PEV) where a euchromatic gene is inserted into a region of transcriptionally inactive heterochromatin, which is thought to spread into the transcriptionally active euchromatin and thereby silencing the gene [19].

Fluorescence in situ hybridisation The presence of chromosomal rearrangements can often be detected by ordi-nary banding techniques like G-banding. However the resolutions of such techniques are limited by the number of chromosome bands and application

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of more advanced methods are needed for the exact mapping of chromosome rearrangements. In situ hybridisation is a method that utilises the base pair-ing of a specific DNA probe to the complementary chromosomes. The method allows chromosome analysis by the direct visualisation of specific chromosome regions, thereby connecting physical and cytogenetic maps. Fluorescence in situ hybridisation (FISH) is a method that uses fluorescently labelled DNA probes (Figure 2). The application of FISH enables the identi-fication of a probe that spans chromosomal rearrangement and is widely used in the investigation of rearrangements associated with human disorders.

Figure 2. Fluorescence in situ hybridisation. Probe DNA is fluorescently labelled and hybridised to the chromosome. Adapted from “Talking Glossary of Genetics”.

Genetic Linkage Genetic linkage is the tendency for genes or genetic markers at specific loci to be inherited together as a consequence of their physical proximity. This fact can be used to study the inheritance of a known locus compared to a disease locus.

Recombination and Genetic distance Genetic linkage is based on recombinations that results from cross-over events between the arms of two homologues chromosomes during meiosis. Recombination allows the chromosomes to increase genetic diversity by shuffling their genetic material. The further apart two loci are on a chromo-some the more likely it is that a recombination event will separate them. The recombination fraction ( ) is the proportion of meioses in which two loci are

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separated by recombination, thus the distance between two loci can be de-termined by the recombination fraction. A single recombination event pro-duces two recombinant and two non-recombinant chromatids, but when loci are well separated there may be more than one crossover between them. Double recombination events can involve two, three, or four chromatids, and the overall effect, averaged over all double crossovers, gives 50% recombi-nants. Therefore, recombination fractions never exceed 0.5 however far apart the loci are (Figure 3).

Figure 3. Single and double recombinations. A crossover takes place between two of the four chromatids of the two homologous chromosomes (black and grey chromo-somes). The alleles A and B are two separate loci. Resulting chromatids carrying the same colour at the two loci are nonrecombinant (N) for these loci, those where the chromatids are different colours are recombinant (R). (A) A single crossover gener-ates two recombinant and two nonrecombinant chromatids. (B) A two-strand double crossover leaves flanking markers nonrecombinant on all four chromatids. (C) A three-strand double crossover leaves flanking markers recombinant on two of the four strands. (D) A four-strand double crossover generates 100% recombinants. The average effect of the three types of double crossover is to produce 50% recombi-nants.

Because of the possibility of double crossovers, recombination fractions are not additive. Consider three loci, A, B and C, the recombination fraction between A – C ( AC) is not equal to the sum of the recombination fractions between A – B ( AB) and B – C ( BC). Furthermore, recombination fractions are also influenced by interference. Interference is the tendency of one crossover event to inhibit further crossover events within the same region of the chromosomes [20].

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If AB is completely independent from BC we say that there is no interfer-ence. In this case the recombination between A – C is equal to:

AC = AB + BC – 2* AB* BC

If there is complete interference recombination fractions are additive because double recombinations does not occur. Also for short distance double re-combinations may be ignored and recombination fractions are nearly addi-tive. However more generally the recombination fractions are not additive and must be converted into map distances. The recombination fraction ( )can be converted to a genetic distance (d) using a mapping function. The genetic distance is measured in Morgans (M)10 or, more often, centi-Morgans (cM). One Morgan equals the average distance in which one crossover oc-curs per meiosis.

The mapping function is dependent on the interference assumed, with complete interference and short distances the mapping function is genetic distance (d) = recombination fraction ( ). With no interference Haldane's mapping function is appropriate:

= 1/2(1 - e-2d) or

d = -1/2 ln(1 -2 )

Kosambi's function adjusts the map distance based on interference which changes the proportion of double crossovers.

= 1/2(e4d - 1) / (e4d + 1) or

d = 1/4 ln(1 + 2 ) - ln(1 - 2 )

Unlike recombination fractions, genetic distances along a chromosome are additive and the total genetic length of the human genome is about 3000 cM. On average the genetic distance of 1 cM equals the physical distance of 1 Mb, however the relationship is not linear. Firstly, recombination in auto-somes is more frequent in females than males, and, secondly, recombination is more frequent closer to the telomeres than near the centromeres [21].

Genetic markers To be able to use a genetic locus as a marker in genetic linkage it needs to be polymorphic and any DNA sequence that is polymorphic and Mendelian can

10 In honor of Thomas Hunt Morgan (1866-1945). For his discoveries concerning the role played by the chromosome in heredity, he was awarded the Nobel Prize in Physiology or Medicine in 1933.

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be used as a marker. The usefulness of a genetic marker is dependent on the informativeness of the marker. The mean heterozygosity of a marker is used to measure the informativeness. The heterozygosity of a marker with i alleles is calculated using the formula:

1 - (p12 + p2

2 + p32 + . . . + pi

2)

Where pi is the frequency of the i:th allele. The heterozygosity is the propor-tion of individuals that will be heterozygous for the marker.

MicrosatellitesMicrosatellites are a small number of short tandem repeats (STR) of very simple sequence, usually 1-4 bp. The length of the tandem repeat is highly variable within the population which is vital for the use of microsatellites in linkage analysis. This has made microsatellites the genetic marker of choice for most applications since their discovery in 1989, including genetic map-ping and studies of evolutionary connections between species and popula-tions [22, 23].

Single Nucleotide Polymorphisms Single nucleotide polymorphisms (SNPs) is any polymorphic variation of a single nucleotide and are the most common type of DNA sequence varia-tions found in humans with an occurrence once every 500 to 1,000 bp. For a single nucleotide substitution to be classified as a SNP it must exist in at least one percent of the population. The even distribution of SNPs through-out the human genome, combined with their frequency and stability, make them valuable as genetic markers [24]. Many genetic diseases are either caused by or closely associated with specific SNPs.

Linkage Analysis LOD score The statistical measure of genetic linkage is called the logarithm of odds(LOD) score (Z). The LOD score is the logarithm of the odds that the loci investigated are linked rather than unlinked. Linkage is said to be accepted when Z > 3 indicating 1:1000 odds for linkage, or rejected when Z < -2, indicating 1:100 against linkage. Values of Z between -2 and 3 is said to be inconclusive [21, 25]. It has been argued that a LOD score of 3 is insuffi-cient to guard against false positive results when investigating complex traits. Therefore, a minimum LOD score of 1.9 (P = 1.7x10-3) and 3.3 (P = 4.9x10-5) has been suggested as thresholds for suggestive and significant LOD scores, respectively, when dealing with complex traits [26]. Even though the goal is to find a positive LOD score, rejected loci tells us where the disease is not, information that can be used for exclusion mapping. Ex-

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clusion mapping is particularly useful for excluding possible candidate genes without the labour of mutation screening.

Parametric and non-parametric linkage analysis Standard LOD score calculations uses parametric linkage analysis and re-quires information regarding mode of inheritance, penetrance and allele fre-quencies. In two-point linkage analysis the phenotype data compared to al-lele data at one marker locus is used for LOD score calculations, whereas in multipoint linkage analysis the phenotype data is compared to allele data for several marker loci.

Non-parametric linkage analysis is a model-free method which does not require information about the mode of transmission of the disease. Non-parametric methods looks for alleles shared by affected only and does not require unaffected siblings.

Association Study Association study is a non-parametric method that test for the association of an allele to the disease in hereditary disorders. Individuals that share a com-mon ancestor to an ancestral mutation are likely to share also alleles at loci close to the disease gene. The presence of a disease gene located near a marker locus may cause linkage disequilibrium (LD), or allelic association,between the marker and the disease loci in isolated populations. This hap-pens when a particular allele at a loci occur together with the disease at a frequencies significantly different from that predicted from the allele fre-quency in the normal population. The extent of LD decreases exponentially with time with a rate proportional to the recombination fraction. The easiest way to test data sets for LD is to use standard 2 or Fisher exact test for two-by-two contingency tables in a case-control association study [27]. Another simple measure of LD is to calculate the allelic excess (Pexcess) of an associ-ated marker allele [28, 29].

Pexcess = (Paffected – Pcontrol) / (1 – Pcontrol)

Where Pcontrol is the frequency of the selected allele at the marker loci in normal chromosomes, and Paffected is the frequency of the selected allele in chromosomes carrying the disease mutation. Pexcess equals 0 when no LD is detected, i.e. frequency of the allele is equal in patients and control.

Haplotype analysis Closely adjacent markers in linkage disequilibrium will constitute a set of alleles co-segregating with the disease phenotype, forming an ancestral hap-lotype. This haplotype associated with the ancestral mutation will be broken down by recombinations over time, and the minimal shared haplotype in affected individuals can be used to define disease associated regions [30].

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Present Investigations

The goal of this thesis has been to use positional cloning methods to identify susceptibility genes or loci for three distinct disorders, obesity, ichthyosis and Meniere’s disease. The basis has been a balanced translocation associ-ated with obesity in a single two-generation family, a probable founder ef-fect of the autosomal inherited disorder ichthyosis type IV, and genetic ho-mogeneity in three large Swedish families with Meniere’s disease.

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Aims

ObesityI To clone the chromosomal breakpoints on chromosome 4 and 15

associated with obesity II To identify possible genes affected by the translocation

Ichthyosis Prematurity Syndrome (IPS) I To restrict the subchromosomal region for the IPS gene by linkage

analysis.II To perform fine mapping and association of the IPS locus III To identify the gene responsible for IPS

Meniere’s Disease (MD) I To find the subchromosomal region for the MD gene by linkage

analysis.II To exclude previously proposed MD loci and to show genetic ho-

mogeneity by including additional families III To identify the gene responsible for MD

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Obesity

IntroductionObesity [MIM 601665] is a highly prevalent multigenic trait that contributes to major health problems in the Western society. The incidence of obesity has reached epidemic levels and patients with severe obesity suffer not only from the direct physical and psychological consequences of overweight but also from increased risk for heart disease, diabetes, hypertension, and certain types of cancer. Current obesity therapies have proven largely ineffective and there is an urgent need to define the aetiology of this disease in order to initiate rational drug development. Obesity appears when energy intake ex-ceeds energy expenditure which leads to an abnormal accumulation of fat in the adipocyte tissue. Both genetic and environmental factors contribute to this multifactorial condition [31].

GeneticsCandidate genes for obesity can be involved in three fundamental mecha-nisms; (i) relative increase in energy intake, (ii) relative decrease in energy expenditure and (iii) preferential partitioning of ingested calories to fat stor-age. Animal models have shown that defects in genes involved in any of these mechanisms are sufficient to cause an obese phenotype [32-35].

In human, seven genes have been identified that are related to obesity in cases with monogenic non-syndromic obesity [36]. Six of these genes are related to the leptin pathway [37-42]. The hormone leptin (LEP) induces a cascade that regulates food intake and energy expenditure, as well as feeding efficiency and the partitioning of fuel stores into fat [43]. The most recent gene to be associated with monogenic obesity in human encodes the tran-scription factor Drosophila single-minded gene 1 (SIM1). This gene was identified from a balanced chromosomal translocation and haploinsuffi-ciency for the gene causes obesity in mice [44, 45].

SubjectsWe have identified a family comprising of two parents and two children. Cytogenetic investigation of the family members revealed that three indi-

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viduals, mother and the two children, are carriers of a balanced t(4;15) trans-location. The father has a normal karyotype.

HypothesisThe identified inherited balanced chromosomal translocation is associated with severe obesity in our family. We hypothesise that the phenotype in our family is caused by the translocation, and that cloning of the translocation breakpoint will allow us to identify candidate genes for obesity.

ResultsPaper I BackgroundThe mother and her two children have a body mass index (BMI) of 41-49 (normal 19-25). Chromosome analysis revealed a balanced reciprocal trans-location t(4;15) in the three affected individuals. The phenotype of this fam-ily is presented as well as the physical mapping and the molecular charac-terization of the chromosomal breakpoints on chromosomes 4q22.3 and 15q21.3, respectively.

ResultsThe clinical features of the affected individuals as well as the physical map-ping and cloning of the chromosomal breakpoints is presented. A detailed characterisation of the chromosomal breakpoints at chromosome 4 and 15 revealed that the translocation is almost perfectly balanced with a very short insertion/deletion. Sequence analysis did not reveal any sequences known to promote translocations [46]. The breakpoint regions do not overlap with any known obesity genes or loci, but interestingly the presence of a microdele-tion-syndrome involving obesity at 15q21 which would in fact overlap with the breakpoint region on chromosome 15 has been reported [47-50]. The chromosome 15 breakpoint is positioned in intron 1 of the RAR-related or-phan receptor A isoform 1 (RORa1) isoform 1, which could propose hap-loinsufficiency of this isoform. The chromosome 4 breakpoint is positioned between two known genes, the unc-5 homolog B (UNC5C) and the pyruvate dehydrogenase (lipoamide) alpha 2 (PDHA2), but no gene is directly af-fected on this chromosome. In addition a fusion gene between RORa1 and UNC5C is created on the chromosome 4 derivate. Expression analyses reveal that the RORa and the fusion gene are expressed in adipocytes, but not UNC5C and PDHA2.

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ConclusionThe rearrangement of the RORa gene predicts the loss of isoform 1 (RORa1) which is implicated in the regulation of adipogenesis and lipoprotein me-tabolism [51, 52]. We hypothesize that the obesity in this family is caused by i) haploinsufficiency for RORa1 or, ii) a gain of function mechanism medi-ated by the RORa1-UNC5C fusion transcript.

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Ichthyosis Prematurity Syndrome (IPS)

IntroductionAutosomal recessive congenital ichthyosis (ARCI) is a clinically and geneti-cally a heterogeneous group of inherited disorders of keratinization [53].

Ichthyosis congenita IV is a rare form of ARCI and is clinically known as the ichthyosis prematurity syndrome (IPS [MIM 608649]). Key features are mid-trimester complicated pregnancy with premature birth of a child with thick caseous desquamating epidermis, respiratory complications and eosi-nophilia recovering into a lifelong non-scaly ichthyosis with atopic manifes-tations. The skin shows a cobble-stone like surface, particularly on distal extremities and a leathery-like thickening of the skin on lower back/rima. In addition hypereosinophilia is shown in the patients [54, 55]. The relatively high incidence of IPS in the 3 counties of middle Norway with a population of 600,000 suggests a strong and ancient founder effect and the mutation associated with IPS is now carried by 2% of the population in this region [56-58].

GeneticsTo date genes corresponding to five loci have been identified that underlie ARCI, and two additional ARCI gene loci have been assigned (Table 1). The genes associated with ARCI are involved in the formation of lipid envelope, fatty acid metabolism or lipid transportation [59-70].

Table 1. ARCI loci and genes.

ARCI Loci Gene

LI1 [MIM 242300] 14q11 TGM1 [59, 60] LI2 [MIM 601277] 2q33-35 ABCA12 [61-63] LI3 [MIM 604744] 19p12-q12 [64] LI5/NCIE1 [MIM 606545/242100] 17p13 ALOXE3 and ALOX12B [65-67] NNCI [MIM 604781] 19p13.2 [68] NCIE2 [MIM 604780] 3p21 CGI-58, or ABHD5 [69] 5q33 Ichthyin [70]

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SubjectsTwenty families comprising 1-2 members affected by IPS were identified. In 17 families samples were obtained from patients and at least one affected and one healthy or affected sibling. Three families comprising only one af-fected child with no siblings were included for haplotype analysis. Alto-gether, 25 affected family members and 18 healthy siblings were available for DNA-studies (Figure 4). Sixteen families originated from a defined re-gion of middle Norway and four from the adjacent region of middle Sweden. None of the families are known to be closely related and no consanguinity was ascertained. The ultrastructural findings were consistent with ichthyosis congenita type IV in all patients.

Figure 4. Pedigrees of IPS families analysed in this study.

HypothesisThe high prevalence of IPS in the adjacent middle parts of Norway and Sweden indicates a possible common ancestor for the disease in this region. Firstly, we wanted to use linkage analysis to map the disease loci by using informative families with IPS from this region. Secondly, we wanted to de-fine a possible ancestral haplotype associated with IPS in affected individu-als.

ResultsPaper II SubjectsWe collected fourteen families originating from a defined region of middle Norway and the adjacent region of middle Sweden. Of 14 Norwegian and 2 Swedish families, 13 were informative for linkage studies.

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ResultsWe have performed a genome wide linkage analysis in 13 informative fami-lies affected by IPS. A significant linkage was found with the STR D9S778 on chromosome 9q34 with a maximum LOD score of 3.73 ( = 0.0) (Table 2). Haplotype analysis and meiotic recombinants restricted the genetic inter-val to a 12 cM region between D9S250 and D9S63.

Table 2. Combined Two-Point LOD Scores at Different Recombination Fractions for Markers on Chromosome 9q33.3-34.13 Calculated on all Thirteen IPS Families.

Two-Point LOD Score at =

Marker .000 .001 .010 .050 .100 .200 .300 .400 D9S302 - -1.977 -0.063 0.953 1.085 0.809 0.415 0.113 D9S1116 - -0.327 0.647 1.181 1.207 0.876 0.450 0.122 D9S250 - -0.777 1.106 1.981 1.942 1.341 0.672 0.181 D9S1881 2.879 2.871 2.799 2.475 2.066 1.283 0.617 0.163 D9S778 3.731 3.721 3.623 3.186 2.646 1.630 0.783 0.206 D9S1840 1.492 1.488 1.444 1.252 1.023 0.612 0.287 0.075 D9S117 3.056 3.046 2.956 2.560 2.083 1.231 0.570 0.147 D9S1825 1.682 1.684 1.691 1.637 1.463 0.984 0.496 0.134 D9S1789 1.800 1.796 1.760 1.583 1.340 0.843 0.408 0.108 D9S1798 2.037 2.033 1.995 1.815 1.503 1.020 0.508 0.127 D9S1821 1.755 1.750 1.704 1.501 1.247 0.766 0.365 0.096 D9S112 3.004 2.995 2.906 2.520 2.060 1.236 0.583 0.152 D9S904 0.859 0.859 0.851 0.792 0.684 0.431 0.206 0.054 D9S918 2.402 2.396 2.337 2.064 1.709 1.032 0.484 0.126 D9S61 3.004 2.995 2.906 2.520 2.060 1.236 0.583 0.152 D9S1795 0.846 0.851 0.885 0.926 0.860 0.594 0.302 0.082 D9S63 3.430 3.422 3.345 2.992 2.534 1.617 0.798 0.214 D9S1863 - -2.402 -0.477 0.591 0.788 0.632 0.334 0.092 D9S915 - -3.373 -1.400 -0.136 0.266 0.399 0.259 0.079 D9S1198 - -1.625 0.284 1.279 1.378 1.021 0.535 0.149

Within this interval a critical region was identified by allelic association. Investigation of the haplotypes surrounding the three markers revealed two possible core haplotypes in the families. The two haplotypes was expanded using telomeric and centromeric markers. The core haplotypes where de-fined using markers D9S1798-D9S1821-D9S112-D9S904-D9S918-D9S61-D9S1795. The two central markers D9S904 and D9S918 did not show asso-ciation and separates the two possible core haplotypes (Figure 5). The com-bined results from linkage, association and haplotype investigation restrict the locus for IPS to a 1 Mb region at 9q33.3-34.13 between D9S112 and D9S918.

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Figure 5. Shared haplotype in IPS families used in Paper I. A (boxed) and B (grey) indicate the two separate core haplotypes. Marker alleles in bold indicate markers showing allelic association (p < 0.05).

ConclusionWe were able to restrict the IPS gene locus to a genetic interval of 9 Mb by meiotic recombinants with no indication of genetic heterogeneity. Haplotype analysis suggests one or two founder chromosomes in the population studied represented by two separate haplotypes. The minimal shared region of the haplotypes is only 1 Mb and contains six genes. We expected a single com-mon ancestor haplotype for the mutation in all families, but the results indi-cate two haplotypes which imply that there may be two founder mutations. One possible explanation is that historical recombination events have changed the original haplotype at a resolution beyond the markers used and a map with a higher resolution is needed to define shared regions and haplo-types within the IPS loci. Genetic markers will also undergo spontaneous mutation over time leading to altered haplotype which is important to re-member when analysing haplotypes. The mutation rate of a marker is associ-ated with the heterozygosity of that marker. Alternatively, a mutant allele may have shifted haplotype by a historic gene conversion resulting in two separate haplotypes for a single mutation. If one consider the possibility of two separate haplotypes associated with IPS, all patients share a region be-tween D9S112 and D9S918, containing 16 known genes or predicted tran-scripts.

Paper III BackgroundIn this paper we wanted to further define the IPS region by creating a marker set with higher resolution. Furthermore we wanted to use the new markers to perform additional haplotype analysis and association studies to define the two possible core haplotypes. The family material was expanded to include three additional informative families, and one healthy sibling was recruited in a former uninformative family. In total our family material now consists of 17 families that are informative for linkage analysis and an additional

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three families with only one affected child that can be used for allelic asso-ciation and haplotype analysis (Figure 4).

ResultsNew polymorphic microsatellite markers where created from repeat regions in the IPS loci. A haplotype map with a marker density of 0.3 Mb could be created. Haplotype analysis refined the centromeric recombination event and restricted the linked region to 5.8 Mb. Within the IPS loci two separate highly associated regions was discovered by allelic association (Fisher exact t-test; p < 10-3). To identify a common disease haplotype in these two candi-date regions we calculated allele frequencies in affected and control haplo-types. We would expect that marker alleles associated with IPS within this region to have a high carrier frequency in affected individuals and adjacent markers with similar high carrier frequencies would constitute a shared hap-lotype. We identified a shared haplotype consisting of three consecutive markers (CAA13-ATTT10-D9S260) with an allelic excess of >0.90 (Pexcess)(Figure 6). The frequency of the shared three-marker haplotype in affected is 0.95 (Paffected) and 0.175 in normal control chromosomes (Pcontrol), which cor-responds to an allelic excess (Pexcess) of 0.94 for the haplotype (Table 3). The region showing high allelic excess, restricted by markers D9S61 and D9S121, covers 231 kb and contains seven genes. The average haplotype length on affected chromosomes is 2.0 Mb which corresponds to a genetic distance of 3.42 cM for this region. This proposes a common ancestor 58 generations ago for this haplotype.

Figure 6. Shared haplotype in IPS families used in Paper II. Gray marker alleles indicate possible core haplotypes. Pexcess is indicated for all markers. Note: The marker alleles for STR D9S1795 have been renumbered in Paper II.

Table 3. Distribution of Combined Haplotypes for D9S61-CAA13-ATTT10-D9S260-D9S121-D9S752. The possible core haplotype consists of marker CAA13-ATTT10-D9S260 and creates the haplotype 2-2-1.

Number (%) of

Haplotype Affected [N=40] Control [N=40] Pexcess

3-2-2-1-x-y-z 28 (70.0) 3 (7,5) 0.62 o-2-2-1-x-y-z 38 (95.0) 7 (17.5) 0.94 o-2-2-1-7-y-z 33 (82.5) 2 (5.0) 0.77 o-2-2-1-7-6-z 28 (70.0) 1 (2.5) 0.67 o-2-2-1-7-6-8 20 (50.0) 1 (2.5) 0.47 Other 2 (5.0) 33 (82.5)

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ConclusionWithin the IPS loci, we identified a core haplotype represented by three marker alleles highly associated with the disease. The haplotype has a high carrier frequency among affected, which indicate a possible founder muta-tion within the shared haplotype. The average shared haplotype is 3.42 cM, which proposes a common ancestor 58 generations ago corresponding to approximately 1500-1800 years. The region showing high allelic excess contains seven genes that could be regarded as candidates for IPS based on their position within the shared region.

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Meniere’s Disease (MD)

IntroductionMeniere’s disease (MD [MIM 156000]) is characterised by spontaneous attacks of vertigo, fluctuating sensorineural low frequency hearing loss, aural fullness, and tinnitus. These phenotypes may be accompanied by any of a range of secondary symptoms that include nausea, vomiting, diarrhoea, and nystagmus. Endolymphatic hydrops is considered to be a pathological factor in the aetiology of Meniere’s disease [71]. The pathologic process involves distortion of the membranous labyrinth with the formation of endolymphatic hydrops, the accumulation of endolymph in the inner ear that leads to swell-ing of the vestibular labyrinth. Hydrops arise as a result of destabilisation of natural regulation of endolymph through either overproduction or reduced absorption. Regulation of endolymphatic fluid volume seems to be con-trolled by ion-channels in the stereocilia and the endolymphatic sac [72]. However endolymphatic hydrops alone is insufficient to explain the patho-physiology of Meniere’s disease and dysfunction of many structures of the inner ear has been proposed to be involved to create the symptoms of MD [73].

GeneticsThere is a genetic disposition of Meniere’s disease and the reported fre-quency of familial MD (FMD) opposed to sporadic MD (SMD) is approxi-mately 5-14% [71, 74-77]. The reported inheritance of FMD follows an autosomal dominant pattern [77, 78]. A familial subset of MD, consisting of 46 families with a total of 118 members affected by MD in two or more gen-erations, supports a dominant inheritance pattern and shows a calculated penetrance value of 60% [77, 79]. Epidemiological surveys conducted in a Swedish population estimate the prevalence of Meniere’s disease to ap-proximately 1 in 2,000; this figure coming from a homogenous population has been considered the most reliable [80, 81]. The phenomenon of anticipa-tion has been observed in some extended pedigrees were for successive gen-erations there is an earlier age of onset, but in the case of MD not an increase in severity of the phenotype [78, 82]. The genetic cause of MD remains un-defined with no clear association to any candidate genes even though COCH mutations has been proposed in patients with MD-like phenotype [71, 83-86].

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SubjectsThree families with segregating for MD in a dominant pattern were identi-fied. The families originated from middle/southern Sweden with no known relationship between the pedigrees. In total 13 affected and 8 unaffected members from the MD families where used in the study.

HypothesisThe molecular basis of both the sporadic and inherited forms of MD remains undefined and no gene behind the disease has yet been mapped. One possi-ble reason is that most reported pedigrees of FMD are relatively small in terms of affected individuals and rarely extend beyond two or three genera-tions. Reduced penetrance and genetic heterogeneity may be other compli-cating factors and the use of larger pedigrees with multiple affected is one way to overcome these problems for linkage analysis.

To deal with the difficulties with the identification of MD genes, we wanted to collect larger families with well defined inheritance of the disease to use for linkage analysis.

ResultsPaper IV BackgroundWe have identified a large Swedish family with inherited Meniere’s disease segregating over five generations. We wanted to map the loci for MD by linkage analysis using this family and to verify the results by using two addi-tional independent families with inherited MD.

ResultsThis analysis suggested a single chromosome region at 12p12 linked to MD in all three families. Further analysis using additional markers in this region revealed a haplotype consisting of seven markers that is identical among affected members of family 1 and 2, proposing a common ancestor for this haplotype. Additional polymorphic markers and recombination events at TA23GA22 and D12S301 in family 2 and 3, respectively, restricted the re-gion to 463 kb using all three families. Linkage analysis showed a highest cumulative lod score of 3.46 for marker TA171 using all three families (Ta-ble 3).

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Table 4. LOD score calculations on markers on chromosome 12p12. All results are calculated at = 0 using full penetrance. Results in bold are markers where linkage could be confirmed by segregation analysis.

Marker DeCode STS Family 1 Family 2 Family 3 Tot

D12S391 12341 - - -2,70 -D12S1630 35,25 16775 -2,68 0,46 0,05 -2,18 AFM338wh5 16899 0,04 - 0,00 -D12S373 35,32 16906 0,74 0,22 -2,70 -1,74 D12S363 35,32 17547 2,20 0,40 -2,70 -0,09 D12S1595 17993 1,66 0,72 0,38 2,76 D12S301 18140 1,11 -0,12 -2,70 -1,71 TA35 18191 0,16 0,86 0,12 1,15 TA171 18206 2,10 0,98 0,38 3,46 GT11 18358 0,21 0,59 0,05 0,84 TA25 18503 0,06 0,18 0,27 0,50 TA23GA22 18603 1,72 - 0,15 -GATA20 18664 -1,85 -0,09 -2,70 -4,64 D12S310 36,23 18865 0,69 0,48 -2,70 -1,53 D12S1591 43.83 23985 0,73 - 0,12 -D12S1057 45.46 24568 -1,35 0,98 0,38 0,02 D12S1042 50,66 27539 -2,78 - 0,10 -cen

ConclusionWe mapped the MD locus to chromosome 12p13 using all three families. A shared haplotype extending over 7 Mb was identified in two families indicat-ing a possible common ancestor to MD in these families. Recombination events in two families restricted the linked region to 463 kb, containing only one gene, phosphoinositide-3-kinase, class 2, gamma polypeptide (PIK3C2G). The proposed involvement of phosphatidylinositol 3-kinase (PI-3K) in the signalling cascades that lead to the proliferation of cells in mam-malian balance epithelia makes this gene a good candidate gene for MD [87].

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Discussion

ObesityThis work uses a unique case of a balanced reciprocal translocation in a fam-ily to clone a candidate gene for obesity. By defining the breakpoint regions, we have predicted the loss of one gene allele implicating that association with the phenotype. Furthermore we have identified the formation of a fu-sion gene on one of the derivative chromosomes. Here we show the advan-tages of identifying chromosomal rearrangements as a tool to map genetic diseases. The method has proved to be successful in the identification many genes behind genetic disorders.

Ichthyosis Prematurity Syndrome In this project we used linkage analysis and allelic association in the map-ping of a well defined genetic disorder with a possible common ancestor using family material from an isolated population. The possibility of detect-ing allelic association is dependent on the relationship between families, the resolution of the genetic marker map, and the genetic heterogeneity of the disease. The haplotype detected by linkage disequilibrium in the families are probably a remnant of the haplotype of a possible common ancestor for IPS in this region. By using a family material from an isolated population we show the power of using linkage analysis followed by linkage disequilibrium to study monogenic diseases.

Meniere’s Disease In this project we used three independent MD families with suspected ge-netic homogeneity to map a disease locus. Furthermore we used exclusion mapping to rule out linkage to known and proposed MD genes. By using a well defined family material segregating for the disease over several genera-tions we where able to map the disease locus. Here we show that by assum-ing homogeneity of the disease in our families we where able to use com-bined results from all three families to achieve significant linkage.

Concluding Remarks Positional cloning has been a successful method in the identification of can-didate genes and gene loci for genetic diseases. However positional cloning is not always straightforward and the main importance is to have well de-

37

fined families. To determination whether a disease is genetically derived is not always simple. Complicating factors include reduced penetrance, vari-able expressivity and genetic heterogeneity.

We have successfully used positional cloning to identify candidate genes or loci for three distinct disorders. Candidate genes need to be further associ-ated with a phenotype than by their position in a mapped disease locus, and appropriate genetic studies such as expression pattern, homology to human genes associated with similar phenotypes, or presence of mutations segregat-ing with the disease need to be investigated.

Final Words The discovery of DNA as the molecule containing our genes and later the structure of this molecule is probably the greatest scientific achievement of the last century. The increasing knowledge about the human genome will give us insight in the role of our genes in the development of disease. This knowledge will result in a superior understanding of how to diagnose, pre-vent and treat human diseases. Furthermore a more personal diagnosis, pre-vention and treatment as well as a more accurate prediction of risk can be made based on a person’s individual genetic profile. But at the same time we need to be careful how we use this information and many ethical issues will arise. Also a genuine dialog on genetic issues and the potential adverse con-sequences is needed to ensure openness and greater public understanding of genetics.

I believe that genetic research is not only a tremendously fascinating field to work in but is important in the understanding of how we function as hu-man beings. Even though basically the sequence of our genome is known through the human genome organisation (HUGO) project, our work has just begun in defining the function of our genes and their role in human disease.

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Acknowledgements

Firstly I would like to acknowledge all the patients and families participating in these studies and making them possible,

Niklas Dahl, my professor and supervisor, who introduced me to the marvel-lous world of human genetics,

My research group Clinical Molecular Genetics, foremost Hans U Matsson,my fellow “researcher of the night”, Birgit Carlsson for keeping it all to-gether. Ed Davey thank you for linguistic “last aid” and thereby actually reading the thesis, Lena Marklund, Malin Larsson my Ichthyosian co-worker, Larry Mansouri, Miriam Entesarian and Anne-Sophie Mikkonen.Former group members, Peter Gustavsson, Dima Tentler and NataliaDraptchinskaia, our mentors in the art of working late,

The “Neighbour group”, Professor Claes Wadelius, Mattias U Jansson, Ben-jamin Bakall, Ola Wallerman and Fredrik Asp(e)gren my golf buddies, Me-hdi Motallebipour and Alvaro Rada. Their former, female, members, TowaMarknell, Sophie Ingvast and Petra Sandell,

Everyone at Clinical Genetics, fronted by Karl-Henrik Gustavsson and Göran Annerén, for putting up with us in the research group. Especially Lore8, Anna and Kerstin in the FISH lab where I frequently messed about,

Tobias Gedde-Dahl Jr, for teaching me about ichthyosis and the history of the Norwegian population,

Our collaborators in the obesity oroject at AstraZeneca R&D, above all Bengt Åsling – Terve!,

Carina Frykholm for introducing me to Meniere’s disease.

The girls at the Genome Center for helping out with marker runs.

My students over the years: Christoph, Fredrik, Lisa, Rita, Christin, Ulrika,Kerstin and Kari,

39

Everyone at the Rudbeck Laboratory, Rudbeck Rockar Fett!,

Erik Siira, who moved to Uppsala and started working at the Electronic Pub-lishing Centre at the University just to help me with my thesis, or to quote Douglas Adams again “I love deadlines. I especially like the whooshing sound they make as they go flying by”,

All my friends and relatives who I have been neglecting when working on this thesis,

My Parents Ewa and Sven, you are the greatest, and my sister Lalit and Mat-tias, with Max, Pontus and Gustaf. My brother Johan and Sara, with Isa and Viggo. I love you all.

…last and most, my bestest and most loved Jenny, so sweet, so sweet…

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