Genetics of dementia disorders and ALS

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FACULTY OF MEDICINE

DEPARTMENT OF MEDICAL AND CLINICAL GENETICS UNIVERSITY OF HELSINKI

HELSINKI UNIVERSITY HOSPITAL AND

DEPARTMENT OF PATHOLOGY UNIVERSITY OF HELSINKI HELSINKI UNVERSITY HOSPITAL

GENETICS OF DEMENTIA DISORDERS AND ALS

Liina Kuuluvainen

DOCTORAL DISSERTATION

To be presented for public discussion, with the permission of the Faculty of Medicine of the University of Helsinki, in the in the Small Lecture Hall of the Haartman Institute, Haartmaninkatu 3,

Helsinki, on the 14th of May 2021, at 1 p.m.

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Supervisors

Professor Minna Pöyhönen

Department of Medical and Clinical genetics

University of Helsinki and Helsinki University Hospital Adjunct Professor Liisa Myllykangas

Department of Pathology

University of Helsinki and Helsinki University Hospital

Reviewers

Adjunct Professor Katarina Pelin

Faculty of Biological and Environmental Sciences University of Helsinki

Associate Professor Maria Johansson-Soller Department of Clinical genetics

Karolinska University Hospital, Karolinska Institutet

Opponent

Associate professor Hannele Laivuori Obstetrics and Gynecology

Tampere University Hospital and

Tampere University, Faculty of Medicine and Health Technology

The Faculty of Medicine uses the Urkund system (plagiarism recognition) to examine all doctoral dissertations

ISBN 978-951-51-7221-1 (pbk.) ISBN 978-951-51-7222-8 (PDF) Unigrafia

Helsinki 2021

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ABSTRACT

The burden of dementia and neurodegenerative disorders such as amyotrophic lateral sclerosis (ALS) is vast both on an individual and economic level, as most of these conditions do not have effective treatments and are largely debilitating. Learning more about the pathogenetic mechanisms behind these disorders can aid in discovering new treatment options.

This study aimed to discover the genetic variation of patients with dementia disorders and ALS, and to conjoin this information with clinical and neuropathological phenotype data.

In the first study a causative GRN mutation c.687T>A, p.(Tyr229*) was identified in a Finnish family with autosomal dominant frontotemporal lobar degeneration. The mutation was shown to cause a variable clinical presentation and disease duration. In the second study, the SOD1 c.269C>T, p.(Ala90Val) mutation was identified in a Finnish motor neuron disease patient. The phenotype associated with the mutation included a limb onset disease, long disease course and sensory symptoms. A Finnish cohort of ALS patients showed that the mutation has a reduced penetrance and is the third most common cause of ALS in the Finnish population. Other genetic variants identified in the SOD1 p.(Ala90Val) mutation carriers suggested that oligogenic inheritance can be an important explanation for the reduced penetrance. In the third study the genetics of vascular dementia in a Finnish cohort was examined. The study revealed that COL4A1, COL4A2, and HTRA1 have an important role in cerebral small vessel disease and vascular cognitive decline, in addition to NOTCH3 among Finnish patients. The patients also had variants associated with

neurodegenerative diseases indicating a possible link between the pathogenetic mechanisms of vascular dementia and neurodegenerative diseases. The fourth study showed that a duplication on chromosome 13, which included the COL4A1 and COL4A2 genes, segregated in a Finnish family with an autosomal dominantly inherited cerebral small vessel disease with variable age of onset.

The phenotype was similar to the previously described patients with an upregulation of COL4A1.

This study provided novel information on the genetics of Finnish patients with frontotemporal lobar degeneration, ALS and vascular cognitive impairment, and the clinical and neuropathological phenotypes associated with them.

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TIIVISTELMÄ

Muistisairaudet ja neurodegeneratiiviset sairaudet kuten amyotrofinen lateraaliskleroosi (ALS) aiheuttavat merkittävän taakaan niin yksilölle kuin yhteiskunnallekin, koska näihin vaikeisiin sairauksiin ei useinkaan ole tehokkaita tai parantavia hoitomuotoja. Sairauksien syntyyn

vaikuttavien tekijöiden ja syntymekanismien parempi tuntemus voi auttaa uusien hoitomuotojen kehittämisessä. Tämän tutkimuksen tavoitteena oli selvittää muistisairauksiin ja ALS:n liittyviä geenivirheitä ja yhdistää tämä tieto genetiikasta tietoon kliinisestä ja neuropatologisesta taudinkuvasta.

Tutkimuksen ensimmäisessä osatyössä kuvattiin uusi GRN-geenin muutos c.687T>A, p.(Tyr229*) ja siihen liittyvä kliininen ja neuropatologinen taudinkuva. Muutoksen osoitettiin aiheuttavan vaihtelevan otsa-ohimohkorappeuman taudinkuvan ja -keston. Toisessa osatyössä kuvattiin maailmanlaajuisesti harvinaiseen SOD1-geenin muutoksen c.269C>T, p.Ala90Val liittyvä kliininen ja neuropatologinen taudinkuva ja muutoksen esiintyvyys suomalaisilla ALS-potilailla. Muutoksen todettiin olevan kolmanneksi yleisin ALS:a aiheuttava geenivirhe suomalaisilla potilailla. Potilailla todettiin myös muita geenimuutoksia SOD1-muutoksen lisäksi sopien siihen, että oligogeeninen periytyminen voi olla merkittävä tekijä muutokseen liittyvän alentuneen penetranssin selittäjänä.

Kolmannessa osatyössä tutkittiin verenkiertoperäisen muistisairauden genetiikkaa suomalaisilla potilailla. Tutkimuksessa todettiin COL4A1- COL4A2- ja HTRA1-geenien muutoksien olevan tärkeitä NOTCH3-geenin muutoksien lisäksi suomalaisilla potilailla. Potilailla todettiin myös

neurodegeneratiivisiin sairauksiin liittyvien geenien muutoksia viitaten mahdollisiin yhteisiin syntymekanismeihin näiden sairauksien välillä. Tutkimuksen neljännessä osatyössä osoitettiin COL4A1- ja COL4A2-geenit sisältävän kromosomin 13 duplikaation segregoivan suomalaisessa perheessä vallitsevasti periytyvän pienten suonten taudin kanssa ja kuvattiin tähän liittyvä taudinkuva.

Tämä tutkimus valotti otsa-ohimolohkorappeuman, ALS:n ja verenkiertoperäisen muistisairauden geneettistä taustaa ja geenivirheisiin liittyvää kliinistä ja neuropatologista taudinkuvaa

suomalaisilla potilailla

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ABBREVIATIONS

3’UTR three prime untranslated region 3R three-repeat tau

4R four-repeat tau

ABHD13 abhydrolase domain containing 13 ABHet allele balance for heterozygous calls

ACMG American College of Medical Genetics and Genomics ACTB actin, beta

AD Alzheimer’s disease

ADGRB2/BAI2 adhesion G protein-coupled receptor B2

aFTLD-U atypical frontotemporal dementia with ubiquitin-positive inclusions ALOX15 arachidonate 15-lipoxygenase

ALS amyotrophic lateral sclerosis AMP Association for Molecular Pathology ANG angiogenin

APP amyloid beta precursor protein

ARHGEF10 rho guanine nucleotide exchange factor 10 ARHGEF28 rho guanine nucleotide exchange factor 28 arr array

Aβ42 amyloid beta 42 BBB blood–brain barrier

BIBID basophilic inclusion body disease

bvFTD behavioral variant frontotemporal dementia C1R complement C1r

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C9ORF72 chromosome 9 open reading frame 72

CACNA1A calcium voltage-gated channel subunit alpha1 A

CADASIL cerebral arteriopathy, autosomal dominant, with subcortical infarcts and leucoencephalopathy

CARASIL cerebral arteriopathy, autosomal recessive, with subcortical infarcts and leucoencephalopathy

CBS corticobasal syndrome cDNA complementary DNA Chr chromosome

CNS central nervous system COL4A1 collagen type IV alpha-1 COL4A2 collagen type IV alpha-2 CSF cerebrospinal fluid CT computed tomography

dbNSFP database of Non-Synonymous Functional Predictions DNA deoxyribonucleic acid

EMG electromyography

ExAC Exome Aggregation Consortium

FBXW8 F-box and WD repeat domain containing 8 FFPE formalin-fixed paraffin-embedded FIMM Institute for Molecular Medicine Finland

FS phred-scaled p-value using Fisher's exact test to detect strand bias FTD3 frontotemporal dementia linked to chromosome 3

FTD-MND frontotemporal dementia-motor neuron disease

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FTLD frontotemporal lobar degeneration

FTLD-FUS frontotemporal lobar degeneration with FUS-positive inclusions FTLD-ni frontotemporal lobar degeneration with no inclusions

FTLD-TAU frontotemporal lobar degeneration with tau-positive inclusions FTLD-TDP frontotemporal lobar degeneration with TDP-positive inclusions FTLD-UPS frontotemporal lobar degeneration with ubiquitin-positive inclusions FUS fused in sarcoma

GATK genome analysis toolkit gnomAD genome aggregation database GOM granular osmiophilic material

GRCh37 genome reference consortium human build 37 GRN granulin precursor

hg19 genome reference consortium human build 37 HGMD Human Gene Mutation Database

HTRA1 high temperature requirement serine peptidase 1

IBMPFD inclusion body myopathy with Paget’s disease of bone and frontotemporal dementia

ICD-10 International Statistical Classification of Diseases and Related Health Problems 10th Revision

IHC immunohistochemistry IRS2 insulin receptor substrate 2 kb kilobase

LIG4 DNA ligase 4

MAF minor allele frequency

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MAPT microtubule-associated protein tau

Mb megabase

MELAS mitochondrial encephalopathy, lactic acidosis, and stroke-like episodes MQ RMS Mapping Quality

MQRankSum Z-score from Wilcoxon rank sum test of Alt vs. Ref read mapping qualities MRI magnetic Resonance Imaging

mRNA messenger RNA MYO16 myosin XVI

nfvPPA nonfluent variant primary progressive aphasia NGS next generation sequencing

NIFID neuronal intermediate filament inclusion disease

NINDS-AIREN Neuroepidemiology Branch of the National Institute of Neurological Disorders and Stroke - Association Internationale pour la Recherche et l'Enseignement en Neurosciences

NOB1 NIN1 (RPN12) binding protein 1 homolog NOTCH3 notch receptor 3

NPPA natriuretic peptide A

PADMAL autosomal dominant pontine microangiopathy and leukoencephalopathy PARK2 autosomal recessive juvenile Parkinson disease-2

PCR polymerase chain reaction PET positron emission tomography

POLG DNA polymerase gamma, catalytic subunit PPA primary progressive aphasia

PSEN1 presenilin 1

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PXDNL peroxidasin like QD quality by depth

ReadPosRank sum Z-score from Wilcoxon rank sum test of alt vs. ref read position bias RNA ribonucleic acid

RT-qPCR quantitative reverse transcription PCR SNTG1 syntrophin gamma 1

SNV single-nucleotide variant SOD1 superoxide dismutase 1

SPECT single photon emission computed tomography SPG11 SPG11 vesicle trafficking associated, spastacsin svPPA semantic variant primary progressive aphasia TARDBP tar DNA binding protein

TDP43 tar DNA binding protein THL Terveyden ja hyvinvoinnin laitos TIA transient ischemic attack TMEM106B transmembrane protein 106B TNFSF13B TNF superfamily member 13b TYKS Turun yliopistollinen keskussairaala UBE2D2 ubiquitin-conjugating enzyme E2D 2 UCL University College London

UNC13A unc-13 homolog A

VASCOG Society for Vascular Behavioral and Cognitive Disorders VCI vascular cognitive impairment

VCING Vascular Cognitive Impairment Neuropathology Guidelines

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VICCCS Vascular Impairment of Cognition Classification Consensus Study VQSR Variant Quality Score Recalibration

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LIST OF ORIGINAL PUBLICATIONS

This thesis is based on the following publications and they are referred to in the text by their Roman numerals.

I

Kuuluvainen L, Pöyhönen M, Pasanen P, Siitonen M, Rummukainen J, Tienari PJ, Paetau A,

Myllykangas L. A Novel Loss-of-Function GRN Mutation p.(Tyr229*): Clinical and Neuropathological Features. J Alzheimers Dis. 2017;55(3):1167-1174. doi: 10.3233/JAD-160647.

II

Kuuluvainen L, Kaivola K, Mönkäre S, Laaksovirta H, Jokela M, Udd B, Valori M, Pasanen P, Paetau A, Traynor BJ, Stone DJ, Schleutker J, Pöyhönen M, Tienari PJ, Myllykangas L. Oligogenic basis of sporadic ALS: The example of SOD1 p.Ala90Val mutation. Neurol Genet. 2019 Apr 23;5(3):e335.

doi: 10.1212/NXG.0000000000000335. eCollection 2019 Jun.

III

Mönkäre S, Kuuluvainen L, Kun-Rodrigues C, Carmona S, Schleutker J, Bras J, Pöyhönen M, Guerreiro R, Myllykangas L. Whole-exome sequencing of Finnish patients with vascular cognitive impairment. Eur J Hum Genet (In press)

IV

Kuuluvainen L, Mönkäre S, Kokkonen H, Zhao F, Verkkoniemi-Ahola A, Schleutker J, Hakonen AH, Hartikainen P, Myllykangas L, Pöyhönen M. COL4A1 and COLA42 duplication causes cerebral small vessel disease with recurrent early onset ischemic strokes in a Finnish family. Manuscript

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1. INTRODUCTION

Dementia is a condition in which cognition progressively declines, decreasing the ability to live independently. As the population in Western countries ages, the number of patients suffering from dementia has risen rapidly and is expected to continue to increase (Prince et al., 2013). The most common dementia disorders are Alzheimer’s disease (AD), vascular dementia, dementia with Lewy bodies and frontotemporal lobar degeneration (FTLD) (Prince et al., 2013). AD is the most common cause of dementia in all age groups, the second most common cause of dementia in patients under the age of 70 is FTLD, and vascular dementia in patients over 70 years of age (Feldman et al., 2003). In addition to progressive cognitive decline, a significant amount of patients with FTLD also have motor symptoms such as parkinsonism or a motor neuron disease, indicating a strong connection between these neurodegenerative diseases (Burrell et al., 2011).

Apart from being a common cause of dementia independently, vascular dementia is also frequently a comorbidity of neurodegenerative diseases (Feldman et al., 2003).

There are familial forms of all of these disorders. Although monogenic forms are rare compared to sporadic types, discovering the genetic variation behind these conditions teaches us not only about the familial forms, but also about pathogenetic mechanisms of the sporadic types, and can therefore help in discovering better therapeutics and treatments. As genome wide sequencing has become more accessible in both research and the clinic, we have learned that different variants of the same gene can cause variable phenotypes. An example of this in neurogenetics is NOTCH3, where different mutations in this gene can cause either cerebral small vessel disease CADASIL or Lehman syndrome, which presents as multiple lateral spinal meningoceles (Gripp et al., 2015, Joutel et al., 1996). The same mutation can also cause seemingly different phenotypes, an example of this is the C9ORF72 hexanucleotide repeat expansion mutation, which is the most common genetic cause of both FTLD and ALS in many populations (Majounie et al., 2012). Even before the identification of the C9ORF72 mutation, the connection between these two

neurodegenerative diseases was supported by the fact that some patients suffer from both of these conditions and share common neuropathological findings (Al-Sarraj et al., 2011). Genomic sequencing has also made it apparent that some patients have two different conditions

simultaneously, explaining their complete phenotype (Basel, McCarrier, 2017). Furthermore, some patients have multiple genetic variants or genetic risk factors contributing to their phenotype in addition to one disease causing mutation blurring the line between monogenic and multifactorial disease (Giannoccaro et al., 2017).

Identifying the causal genetic defect(s) in a family enables more accurate and informative genetic counseling not only for the patients but also family members. Discovering the cause of the disorder in a family can relieve anxiety of the unknown and possibly aid in family planning (Basel, McCarrier, 2017). It also provides an efficient and rapid diagnostic tool for symptomatic family members.

This study aimed to discover genetic variation of patients with dementia disorders and ALS, and to combine this genetic information with detailed information of clinical outcomes and

neuropathological phenotypes to learn about the effects of the genetic variations.

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2.REVIEW OF LITERATURE

2.1 Dementia disorders

Dementia is a disorder where cognition declines, impairing daily activities. In the International Statistical Classification of Diseases and Related Health Problems 10th Revision (ICD-10, https://www.who.int/classifications/icd/icdonlineversions/en/ ) dementia is defined as: “ a syndrome due to disease of the brain, usually of a chronic or progressive nature, in which there is disturbance of multiple higher cortical functions, including memory, thinking, orientation, comprehension, calculation, learning capacity, language, and judgement.”

The most common causes of dementia are AD, vascular cognitive impairment, dementia with Lewy bodies and FTLD (Prince et al., 2013). Dementia is a major health issue both humanely and

economically as the cost of dementia globally is over 800 billion US dollars, and is expected to rise as the number of patients suffering from the condition rises with aging populations (Wimo et al., 2017).

2.2 Frontotemporal lobar degeneration

2.2.1 Epidemiology

Epidemiological studies in FTLD have been difficult due to the variability in clinical criteria used for diagnosis until 1998, when the current widely used criteria were established (Neary et al., 1998).

Many studies have relied upon post mortem investigations. One of the most recent studies reported an incidence of approximately 3 per 100 000 person years in the Italian population (Logroscino et al., 2019). A study from Northern Finland showed a one year incidence of almost 6 per 100 000 in the age group of 45-65 years old (Luukkainen et al., 2015). An autopsy study in the US showed that 5% of dementia patients had FTLD (Barker et al., 2002). The point prevalence of FTLD has been estimated to be 0.01-4.6 per 1000 (Hogan et al., 2016).

2.2.2 Clinical features

FTLD is categorized based on the clinical phenotype with behavioral variant frontotemporal dementia (bvFTD) and primary progressive aphasia (PPA) (Rascovsky et al., 2011, Gorno-Tempini et al., 2011). PPA has three main variants, nonfluent or agrammatic, semantic and logopenic (Gorno-Tempini et al., 2011). Behavioral variant frontotemporal dementia (bvFTD) is the most common subtype of FTLD (Hodges et al., 2003). The presenting symptoms in bvFTD are issues with behavior and executive functions and changes in personality (Chare et al., 2014). The age of onset of FTLD is typically under 65 years (Hodges et al., 2003).

Patients with nonfluent or agrammatic PPA have progressive speech production problems and patients with the semantic variant primarily suffer from problems with comprehension of words and have difficulties in naming objects. Nonfluent PPA is slightly less common than the semantic variant (Chare et al., 2014).

As FTLD progresses the clinical features of the different subtypes merge, and global cognitive decline becomes apparent. Motor symptoms also appear. Almost 40% of patients have some

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motor symptoms and approximately 20% have a concurrent motor neuron disease, such as ALS (Burrell et al., 2011). FTLD is progressive and disease duration is usually 5-10 years (Hodges et al., 2003).

Clinical diagnosis has been challenging in the past, but diagnostic criteria based on phenotypes have now been developed (Neary et al., 1998, Gorno-Tempini et al., 2011).

Imaging studies with CT or MRI usually show frontal and temporal lobe atrophy and functional brain imaging with SPECT or functional MRI show hypoperfusion of affected areas (Rosen, H. J. et al., 2002, Le Ber et al., 2006). No diagnostic laboratory tests such as biomarkers are available for FTLD at this time, although serum neurofilament light chain analysis has shown promise for the future (Katisko et al., 2020).

2.2.3 Neuropathology

The macroscopical features of FTLD include brain atrophy, especially in the anterior temporal and frontal lobes; eventually other areas are also affected (Mackenzie, I. R. et al., 2009). FTLD is neuropathologically classified into subtypes based on microscopical findings (Mackenzie, I. R. et al., 2009, Mackenzie, I. R. et al., 2010). FTLD has intracellular inclusions that are usually

immunoreactive to tau (FTLD-TAU) or TDP43 (FTLD-TDP). In about 10-15% of patients with FTLD the inclusions are not immunoreactive to either tau or TDP43. Some of these are immunoreactive to FUS (FTLD-FUS). The ones that are not immunoreactive for FUS are labeled FTLD-UPS because current methods indicate they are only immunoreactive to the ubiquitin proteasome system. FTLD with no visible inclusions and do not react to special histochemical stains or

immunohistochemistry are called FTLD-ni (no inclusions) (Mackenzie, I. R. et al., 2009, Mackenzie, I. R. et al., 2010, Mackenzie, I. R. et al., 2011).

These major subclasses (FTLD-TAU, FTLD-TDP, FTLD-FUS, FTLD-UPS, FTLD-ni) can be further subdivided into subtypes. For example FTLD-TDP is divided to four types (types A-D) according to the morphology and anatomic positions of the TDP43-positive inclusions (Mackenzie, I. R. et al., 2011, Mackenzie, I. R. et al., 2009, Mackenzie, I. R. et al., 2010).

Neuropathology can provide important clues on the genetics of the patient’s disease, with for example GRN mutations usually causing FTLD-TDP pathology type A (Mackenzie, Ian R. A., 2007).

The neuropathological subtypes and their commonly associated phenotypes and genes are listed in TABLE 1

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TABLE 1 Neuropathological subtypes of FTLD and their commonly associated phenotypes and genes. Modified from Lashley et al., 2015, Mackenzie, I. R. et al., 2011.

FTLD subclass Subtype Commonly associated phenotypes Associated genes

FTLD-tau 3R

CBS, PSPS, PNFA, FTLD-MND, svPPA,

bvFTD MAPT

4R

3R and 4R

FTLD-TDP Type A bvFTD, FTD-MND, nfvPPA,CBS GRN, C9ORF72

Type B bvFTD, FTD-MND, nfvPPA C9ORF72

Type C bvFTD, svPPA

Type D bvFTD, IBMPFD VCP

FTLD-FUS aFTLD-U bvFTD

NIFID bvFTD, PSPS,CBS

BIBID

FTLD-UPS FTD3 bvFTD CHMP2B

FTLD-ni

bvFTD: behavioral variant frontotemporal dementia, nfvPPA: nonfluent variant primary progressive aphasia, svPPA: semantic variant primary progressive aphasia, IBMPFD: inclusion body myopathy with Paget’s disease of bone and frontotemporal dementia, FTD-MND: frontotemporal dementia- motor neuron disease, CBS: corticobasal syndrome, aFTLD-U: atypical frontotemporal dementia with ubiquitin-positive inclusions, NIFID: neuronal intermediate filament inclusion disease, BIBID:

basophilic inclusion body disease, FTD3: frontotemporal dementia linked to chromosome 3, 3R:

three-repeat tau, 4R:four-repeat tau.

2.2.4 Genetics

Approximately 50% of patients with FTLD have a family history of the disease and approximately 10% have a clearly autosomal dominant inheritance pattern (Rohrer et al., 2009). The most common genetic cause of FTLD is the C9ORF72 hexanucleotide repeat expansion mutation, which explains about 25% of familial FTLD and about 6% of apparently sporadic FTLD in most Western countries (Majounie et al., 2012). However, this is somewhat variable between populations, as for example in Japan the C9ORF72 expansion mutation is much more rare (Ogaki et al., 2013). After its identification, the function of C9ORF72 and possible pathogenetic mechanisms caused by the mutation have been widely studied, with the results so far suggesting both loss of function and multiple toxic gains of functions (Balendra, Isaacs, 2018).

Other common genetic causes of FTLD are MAPT and GRN mutations (Rohrer et al., 2009). The frequencies of mutations in these genes are also somewhat variable between populations, as for example GRN mutations are the second most common cause of FTLD in most Western countries but are rare in the Finnish population (Krüger et al., 2009). GRN encodes progranulin, a peptide which is a growth factor involved in multiple processes (Paushter et al., 2018). GRN mutations that result in FTLD usually cause haploinsufficiency, so the disease is likely caused by a loss of function mechanism (Cruts et al., 2006). Variants in other genes, such as TMEM106B, which regulates the levels of progranulin, can regulate the penetrance of GRN mutations (Finch et al., 2011). Genes associated with FTLD are listed in TABLE 2.

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TABLE 2 Genes associated with FTLD. Data from Bang, Spina & Miller, 2015 and original publications. GENE (HGNC) MIM # Genomic location (GRCh38) Inheritance pattern Clinical phenotypes (OMIM) Reference C9ORF72 6142609:27546545-27573865 ADFrontotemporal dementia and/or amyotrophic lateral sclerosis 1,MIM105550 (DeJesus-Hernandez et al., 2011, Renton, Alan E et al., 2011) MAPT 15714017:45894381-46028333AD, AR Dementia, frontotemporal, with or without parkinsonism(MIM600274), Pick disease (MIM172700), Supranuclear palsy, progressive(MIM601104), Supranuclear palsy, progressive atypical(MIM260540), Parkinson disease, susceptibility to (MIM168600)

(Wilhelmsen et al., 1994, Hutton et al., 1998) GRN13894517:44345085-44353105 AD,AR

Frontotemporal lobar degeneration with ubiquitin-positive inclusions(MIM607485), Ceroid lipofuscinosis, neuronal, 11(MIM614706), Aphasia, primary progressive (MIM607485) (Baker et al., 2006, Cruts et al., 2006) TARDBP6050781:11012653-11030527 AD

Frontotemporal lobar degeneration, TARDBP-related (MIM612069), Amyotrophic lateral sclerosis 10, with or without FTD (MIM612069) (Borroni et al., 2009, Synofzik et al., 2014) FUS13707016:31180109-31194870AD

Amyotrophic lateral sclerosis 6, with or without frontotemporal dementia(MIM608030), Essential tremor, hereditary, 4 (MIM614782)

(Kwiatkowski et al., 2009, Vance et al., 2009) VCP6010239:35056063-35072667 AD

Inclusion body myopathy with early-onset Paget disease and frontotemporal dementia 1 (MIM167320), Charcot-Marie-Tooth disease, type 2Y (MIM616687), Amyotrophic lateral sclerosis 14, with or without frontotemporal dementia (MIM 613954)

(Watts et al., 2004)

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CHMP2B6095123:87227308-87255555 ADDementia, familial, nonspecific (MIM600795), Amyotrophic lateral sclerosis 17(MIM614696) (Skibinski et al., 2005) TBK160483412:64452104-64502113 AD Frontotemporal dementia and/or amyotrophic lateral sclerosis 4 (MIM 616439), Encephalopathy, acute, infection- induced (herpes-specific), susceptibility to, 8(MIM617900)

(Freischmidt et al., 2015, Pottier et al., 2015) SQSTM16015305:179806392-179838077 AD, AR

Frontotemporal dementia and/or amyotrophic lateral sclerosis 3 (MIM616437), Myopathy, distal, with rimmed vacuoles(MIM617158), Neurodegeneration with ataxia, dystonia, and gaze palsy, childhood- onset(MIM617145), Paget disease of bone 3 (MIM167250)

(Rubino et al., 2012) PSEN110431114:73136435-73223690AD

Pick disease (MIM172700), Dementia, frontotemporal (MIM600274), Cardiomyopathy, dilated, 1U (MIM613694), Alzheimer disease, type 3, with spastic paraparesis and unusual plaques (MIM607822), Alzheimer disease, type 3, with spastic paraparesis and apraxia (MIM607822), Alzheimer disease, type 3(MIM607822), Acne inversa, familial, 3 (MIM613737)

(Sherrington et al., 1995)

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2.2.5 Hypotheses on pathogenesis

The combination of neuropathological information with the genetic data behind FTLD has revealed multiple mechanisms behind FTLD, and many proteins encoded by the genes associated with FTLD seem to function in multiple pathways, illustrating the complexity of the disease. Altered RNA metabolism and protein homeostasis, and protein aggregation are two of the pathological mechanisms discovered (Gascon, Gao, 2014, French, R. L. et al., 2019).

C9ORF72 functions in RNA metabolism, with the C9ORF72 hexanucleotide repeat expansion disrupting nucleocytoplasmic transport and causing the accumulation of double stranded RNA resulting in toxicity (Zhang, K. et al., 2015, Zhang, Y. J. et al., 2019). The C9ORF72 hexanucleotide expansion has also been shown to cause haploinsufficiency, suggesting a loss of function having a pathological effect; C9ORF72 has a role in endosomes and is needed for normal vesicle trafficking and lysosomal biogenesis in motor neurons (Shi et al., 2018). TARDBP mutations cause TDP43 aggregation and RNA interaction has been shown to be important in maintaining TDP43 solubility (French, R. L. et al., 2019). FUS is also involved in RNA processing (Nolan, Talbot & Ansorge, 2016).

MAPT encodes tau protein and mutations in the gene affect intracellular transport and cause pathological protein aggregation (Rademakers, Cruts & van Broeckhoven, 2004). GRN has been implicated in immunological processes and lysosomal degradation (Paushter et al., 2018, Zhou, X.

et al., 2015, Lui et al., 2016, Gibbons et al., 2015).

Immunological mechanisms have recently been widely studied and have shown altered immunological responses in patients with FTLD (Cavazzana et al., 2018). It is suggested that the altered microglial activation causes prohibition of neuronal repair and disrupts the blood brain barrier (BBB). As neuronal repair is disrupted, oxidative damage, mitochondrial dysfunction and synaptic impairment cause neuronal damage (FIGURE 1). The BBB maintains the homeostasis of the central nervous system (CNS) and prevents many neurotoxins from entering the CNS (Chow, B.

W., Gu, 2015). The immunological mechanism was recently reinforced by the discovery with PET imaging that inflammation and protein aggregation co-localize in FTLD patients (Bevan-Jones et al., 2020).

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FIGURE 1 Neuroinflammation in FTLD pathogenesis. Modified from Bright et al., 2019.

2.3 Vascular dementia

Vascular dementia is a severe form of vascular cognitive impairment (VCI). Although it can be the only pathology in a patient with dementia, it often presents as a comorbidity concurrently with other dementia disorders such as AD (Schneider et al., 2007).

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In a US study, the prevalence of vascular dementia was about 2:100 (Plassman et al., 2007). In a UK study, the incidence of dementia after a stroke depended on the severity of the stroke, with the incidence of dementia after one year as high as 34% in those with a severe stroke,

approximately 8% in those with a minor stroke and approximately 5% in those who had had a transient ischemic attack (TIA) (Pendlebury, Rothwell & Oxford Vascular Study, 2019). In the same study the 5-year risk of dementia was also associated with the severity of the initial event and also other factors such as age, baseline cognition, education and diagnosed diabetes (Pendlebury, Rothwell & Oxford Vascular Study, 2019).

VCI can be caused by a symptomatic cerebral event such as a stroke or bleed or clinically silent cerebral vascular events that are only evident in imaging studies. Cerebral small vessel disease, which is a common cause of VCI, can often cause these clinically silent vascular events such as small subcortical infarcts, lacunes and microbleeds and also white matter hyperintensities, perivascular spaces and brain atrophy (Wardlaw et al., 2013). The main features required for diagnosis of VCI in all of the clinical criteria in use are the presence of cognitive impairment and valid evidence of causal cerebrovascular pathology. The evidence of causal cerebrovascular pathology can be related to the clinical phenotype (i.e. focal neurological signs or symptoms), neuroimaging (CT or MRI) or histopathology. The need to exclude neurodegenerative diseases or other processes that explain the whole phenotype are also included in all the criteria.

The main criteria used in clinical and research work are from the Neuroepidemiology Branch of the National Institute of Neurological Disorders and Stroke - Association Internationale pour la Recherche et l'Enseignement en Neurosciences (NINDS-AIREN) (Roman et al., 1993) and the more recent International Society for Vascular Behavioral and Cognitive Disorders (VASCOG) (Sachdev, P. et al., 2014) and Vascular Impairment of Cognition Classification Consensus Study (VICCCS) (Skrobot et al., 2018). As vascular dementia causes other cognitive issues more than just diminishing memory, the VICCCS and VASCOG criteria for major VCI or vascular dementia do not have the mandatory requirement of memory impairment that the older NINDS-AIREN criteria has.

The VICCCS and VASCOG criteria have also added mild VCI into the classification, which the older NINDS-AIRDEN does not have. Recently, a validation study showed that the VASCOG criteria have greater sensitivity compared to VICCCS (Sachdev, P. S. et al., 2019). The VASCOG criteria also recognizes genetic results in the diagnosis as clinical and genetic evidence of cerebrovascular disease is sufficient for a diagnosis of probable vascular cognitive disorder even without neuroimaging (Sachdev, P. et al., 2014).

Vascular cognitive decline has no universally used neuropathological consensus criteria. Several attempts for one have been made. Vascular Cognitive Impairment Neuropathology Guidelines (VCING) has created a model to estimate the likelihood that cerebrovascular disease contributed to a patient’s cognitive impairment (Skrobot et al., 2016). This includes evaluation of cerebral amyloid angiopathy, arteriolosclerosis and cerebral infarcts. According to these evaluations the classification can be specified as low likelihood (<50%), moderate likelihood (50-80%) and high likelihood (>80%) of VCI (Skrobot et al., 2016).

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2.3.4 Genetics

As the risk factors for cognitive impairment after stroke are such as high blood pressure and type 2 diabetes mellitus, the variants in genes affecting these can also be risk factors for VCI (Lo et al., 2019).

There are rare monogenic causes for vascular dementia. The most common and well known is CADASIL (Cerebral Autosomal Dominant Arteriopathy with Subcortical Infarcts and

Leukoencephalopathy) which is caused by NOTCH3 mutations (Joutel et al., 1996). It is autosomal dominant, and clinical features can include migraine with aura in addition to recurrent strokes and cognitive decline (Joutel et al., 1996, Chabriat et al., 1995). Before NOTCH3 sequencing became feasible with more affordable sequencing methods, the first line of testing was often a skin biopsy, as patients with NOTCH3 mutations show granular osmiophilic material (GOM) in vascular smooth muscle cells (Walsh, Perniciaro & Meschia, 2000). HTRA1 mutations cause an autosomal recessive condition similar to CADASIL called CARASIL (Cerebral Autosomal recessive Arteriopathy with Subcortical Infarcts and Leukoencephalopathy) (Hara et al., 2009). In addition to the symptoms of CADASIL, its symptoms include premature hair loss and lower back pain (Hara et al., 2009). Some HTRA1 mutations have been shown to cause an autosomal dominant disease in addition to heterozygous carriers having a higher risk to cerebrovascular disease at a later age (Nozaki et al., 2016, Verdura et al., 2015).

Some 3’UTR mutations of COL4A1 cause cerebral small vessel disease similar to CADASIL (Siitonen et al., 2017, Verdura et al., 2016). Intragenic missense mutations in COL4A1 and COL4A2 genes can also cause cerebral small vessel disease with additional neurological features such as

porencephaly, which can manifest in a fetus during pregnancy (Meuwissen et al., 2015). Missense mutations in these genes can also cause extraneurological features such as opthalmological, nephrological, cardiac and muscular symptoms or lesions (Meuwissen et al., 2015). These extraneurological features have not been associated with 3’UTR mutations of COL4A1 or duplications of COL4A1 and COL4A2 (Low et al., 2007, Siitonen et al., 2017, Saskin et al., 2018, Verdura et al., 2016). There are also some rare causes for monogenic cerebral small vessel disease, which often have additional systemic features (TABLE 3).

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TABLE 3 Genes associated with cerebral small vessel disease. Data from Ilinca et al., 2019, Ikram et al., 2017 and original publications GENE (HGNC) MIM#Genomic location (GRCh38) Inferitance pattern Clinical phenotypes (OMIM) Reference NOTCH360027619:15159037-15200994ADCerebral arteriopathy with subcortical infarcts and leukoencephalopathy 1(MIM125310), Lateral meningocele syndrome (MIM130720), Myofibromatosis, infantile 2(MIM615293)

(Sourander, Walinder, 1977, Dichgans et al., 1998) HTRA160219410:122461552-122514906AR, AD

CARASIL syndrome (MIM600142), Cerebral arteriopathy, autosomal dominant, with subcortical infarcts and leukoencephalopathy, type 2 (MIM616779), Macular degeneration, age-related, neovascular type (MIM610149), Macular degeneration, age-related, 7 (MIM610149)

(Verdura et al., 2015) COL4A112013013:110148962-110307156 AD

Microangiopathy and leukoencephalopathy, pontine, autosomal dominant (MIM618564), Brain small vessel disease with or without ocular anomalies (MIM175780), Angiopathy, hereditary, with nephropathy, aneurysms, and muscle cramps (MIM611773), Hemorrhage, intracerebral, susceptibility to (MIM614519), Retinal arteries, tortuosity of (MIM180000)

(Jeanne, Gould, 2017) COL4A212009013:110307283-110513208ADBrain small vessel disease 2(MIM614483), Hemorrhage, intracerebral, susceptibility to (MIM614519)(Jeanne, Gould, 2017) GLA300644X:101397802-101407924XLFabry disease (MIM301500), Fabry disease, cardiac variant (MIM301500) (Eng, Desnick, 1994) MMACHC6098311:45500228-45513381 ARMethylmalonic aciduria and homocystinuria, cblC type (MIM277400)(Lerner-Ellis et al., 2006) MTHFR6070931:11785722-11806102 AD,AR

Homocystinuria due to MTHFR deficiency (MIM236250), Vascular disease, susceptibility to, Thromboembolism, susceptibility to (MIM188050), Schizophrenia, susceptibility to (MIM181500), Neural tube defects, susceptibility to (MIM601634)

(Goyette et al., 1994)

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TREX16066093:48465829-48467644 AD,AR Vasculopathy, retinal, with cerebral leukodystrophy(MIM192315), Chilblain lupus (MIM610448), Aicardi-Goutieres syndrome 1, dominant and recessive (MIM225750), Systemic lupus erythematosus, susceptibility to (MIM152700)

(Grand et al., 1988, Ophoff et al., 2001) PDCD106091183:167683297-167735809 ADCerebral cavernous malformations 3 (MIM603285) (Bergametti et al., 2005) MMUT 6090586:49430359-49463297 ARMethylmalonic aciduria, mut(0) type (MIM251000)(Ledley et al., 1990) FOXC16010906:1609914-1613896 ADAxenfeld-Rieger syndrome, type 3 (MIM602482), Anterior segment dysgenesis 3, multiple subtypes (MIM601631) (French, C. R. et al., 2014) CCM26079297:44999745-45076469 ADCerebral cavernous malformations-2 (MIM603284) (Liquori et al., 2003) KRIT16042147:92198968-92246099 AD

Hyperkeratotic cutaneous capillary-venous malformations associated with cerebral capillary malformations (MIM116860), Cerebral cavernous malformations-1(MIM116860), Cavernous malformations of CNS and retina (MIM116860)

(Laberge-le Couteulx et al., 1999) ACTA210262010:88935073-88991396ADMultisystemic smooth muscle dysfunction syndrome(MIM611788), Moyamoya disease 5(MIM614042), Aortic aneurysm, familial thoracic 6 (MIM611788)

(Milewicz et al., 2010, Guo et al., 2009) PDE3A123805 12:20369244-20688578 ADHypertension and brachydactyly syndrome (MIM112410)(Maass et al., 2015) ITM2B60390413:48233205-48270356ADDementia, familial Danish (MIM117300), Dementia, familial British(MIM176500), Retinal dystrophy with inner retinal dysfunction and ganglion cell abnormalities(MIM616079)

(Vidal et al., 1999, Vidal et al., 2000) ABCC660323416:16149564-16223616ARPseudoxanthoma elasticum, forme fruste(MIM177850), Pseudoxanthoma elasticum (MIM264800), Arterial calcification, generalized, of infancy, 2 (MIM614473)

(Bergen et al., 2000, Le Saux et al., 2000, Ringpfeil et al., 2000) HSD11B261423216:67431120-67437552ADApparent mineralocorticoid excess (MIM218030) (Wilson et al., 1998)

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GAA60680017:80101534-80119880ARGlycogen storage disease II (MIM232300) (Martiniuk et al., 1986) CST360431220:23626705-23637954 ADCerebral amyloid angiopathy (MIM105150), Macular degeneration, age-related, 11 (MIM611953)(Abrahamson et al., 1989) CTSA61311120:45890143-45898819ADGalactosialidosis (MIM256540) (Bugiani et al., 2016) APP10476021:25880549-26171127ADCerebral amyloid angiopathy, Dutch, Italian, Iowa, Flemish, Arctic variants (MIM605714),Alzheimer disease 1, familial (MIM104300) (Levy et al., 1990) CBS61338121:43053189-43076860ARThrombosis, hyperhomocysteinemic (MIM236200),Homocystinuria, B6-responsive and nonresponsive types (MIM236200) (Kelly et al., 2003) ADA260757522:17178789-17221853ARVasculitis, autoinflammation, immunodeficiency, and hematologic defects syndrome (MIM615688),Sneddon syndrome (MIM182410) (Zhou, Q. et al., 2014) ATP7A300011X:77910655-78050394 XLSpinal muscular atrophy, distal, X-linked 3(MIM300489),Occipital horn syndrome (MIM304150),Menkes disease (MIM309400) (Kaler et al., 1994)

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VCI is caused by small or large cerebral vascular events. They can be either infarcts or bleeds, or both. The mechanisms behind the genetic forms of cerebral small vessel disease might be at least somewhat similar to the sporadic forms.

NOTCH3 dysfunction causes extracellular matrix proteins to be abnormally recruited and therefore abnormalities in the extracellular matrix of the vessels occur (Monet-Lepretre et al., 2013). HTRA1 pathogenic mutations have shown loss of function in protease activity, which leads to increased TGF-β family signaling, which in turn are involved in multiple functions in vascular endothelia (Hara et al., 2009). COL4A1 and COL4A2 encode the alpha1 and alpha2 subunits of type IV collagen, respectively (Meuwissen et al., 2015). Type IV collagen is a part of nonfibrillary collagen, which is the main component of the basement membrane vascular endothelia among many other tissues (Meuwissen et al., 2015). One mechanism behind the disease is a potassium

channelopathy that causes an inability of the vessels to contract in response to pressure (Dabertrand et al., 2015). There are also changes in the blood-brain barrier (BBB) which in turn causes metabolic changes in the brain (Rustenhoven et al., 2016, Siegenthaler et al., 2013).

Different pathogenetic mechanisms causing VCI in cerebral small vessel disease are outlined in FIGURE 2.

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FIGURE 2 Pathogenetic mechanisms in VCI. Modified from Ihara, Yamamoto, 2016.

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2.4 Other dementia disorders

2.4.1 Alzheimer’s disease

AD is the most common dementia disorder (Prince et al., 2013). Clinically, AD usually presents as episodic memory loss and additional cognitive symptoms (Morris et al., 2014). Compared to FTLD and vascular dementia, AD has biomarkers that can be used in diagnosis. Patients with AD have below normal levels of Aβ42 and above normal levels of tau protein in their CSF (Tapiola et al., 2009). These biomarkers are associated with neuropathological changes as the two characteristic lesions in AD, senile plaques and neurofibrillary tangles contain Aβ42 and tau, respectively (Hyman et al., 2012). The lesions are found in the limbic regions in the early stages of the disease but appear also in other regions of the brain in later stages of the disease (Hyman et al., 2012).

2.4.2 Dementia with Lewy bodies

The neuropathological changes in dementia with Lewy bodies include Lewy bodies which are abnormal deposits of α-synuclein, and neurites immunoreactive to α-synuclein (Hyman et al., 2012) . Clinically, dementia with Lewy bodies presents as cognitive impairment that fluctuates and difficulties with problem solving and attention, and visuospatial issues are prominent early in the disease course (McKeith et al., 1996). Patients also suffer from visual hallucinations and

parkinsonism (McKeith et al., 1996).

2.4.3 Rare dementia disorders

There are also many rare progressive dementia disorders, such as prion disease, Huntington’s disease and chorea-acanthocytosis (MacDonald et al., 1993, Owen et al., 1989, Rampoldi et al., 2001). These conditions can be sporadic or monogenic or have both of these subtypes. It is also noteworthy that many patients suffer from two conditions concurrently, for example many elderly patients have both AD and VCI.

2.5 ALS

The incidence of ALS in population based studies ranges from 1:100 000 in Europe and North America, and 0.5:100 000 in Asia (Cronin, Hardiman & Traynor, 2007). The incidence might be lower in some populations such as the African population (Cronin, Hardiman & Traynor, 2007).

There is also some variation in the incidence within and between countries. For example, there has been a significantly higher incidence of ALS in Guam, an island in the western Pacific Ocean (Arnold, Edgren & Palladino, 1953, Koerner, 1952, Mulder, Kurland & Iriarte, 1954). The

geographical variation is evident also in Finland as there is a regional clustering of ALS in Southeast Finland (Murros, Fogeholm, 1983). The incidence of ALS is higher in males than females (Ingre et al., 2015). ALS incidence increases after age 40, the peak age for the incidence is 65-74 and declines in older age groups (Chio et al., 2011).

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ALS is a motor neuron disease that affects both the upper and lower motor neurons. Aside from genetic ALS, there is no single diagnostic laboratory test currently in use for the disease and therefore the diagnosis is most often based on clinical features and EMG results. The El Escorial criteria are the most widely used consensus clinical criteria in the diagnosis of ALS (Brooks, 1994).

The El Escorial criteria has categories for the certainty of a diagnosis ranging from suspected to definitive based on motor neuron signs (Brooks, 1994). Autopsy studies have shown that the diagnosis of definite ALS was confirmed pathologically in 100% of cases whereas only 33% of suspected ALS was confirmed pathologically (Chaudhuri et al., 1995). Suspected ALS has been removed from the revised El Escorial criteria (Brooks et al., 2000). The issue with clinical diagnostic criteria is that the diagnosis requires evidence of a progressive disease, which often delays diagnosis and therefore could potentially delay treatment (Traynor et al., 2000). 90% of ALS patients meet the clinical criteria of definite or probable ALS during their lifetime (Traynor et al., 2000).

ALS is classically divided into a bulbar and limb onset disease, depending on the site of first symptoms. Bulbar ALS usually starts with dysarthria. Limb onset ALS is further defined to lower or upper limb onset. Usually the symptoms start in the distal rather than the proximal muscles of the limbs. ALS causes weakness and atrophy of the muscles. Most patients have fasciculations. Upper motor neuron signs (i.e. Babinski and Hoffman signs, the jaw jerk) may be difficult to detect as lower motor neuron dysfunction can mask them (Brooks et al., 2000).

The duration of the disease varies, but is usually 3-5 years (del Aguila et al., 2003). The cause of death is usually related to respiration as ventilation muscles deteriorate (del Aguila et al., 2003).

Approximately 50% of patients have some cognitive issues and a significant portion of those have cognitive decline that reaches the level of dementia, which is usually FTLD type (Lomen-Hoerth et al., 2003).

The neuropathology of genetic and sporadic ALS is usually quite similar. The brain is fairly unaffected if there is no dementia, while the anterior horns of the spinal cord are atrophic.

Histopathologically there is a loss of neurons in the motor cortex and in the anterior horn of the spinal cord, and in the hypoglossal nucleus. There is also a loss of myelinated axons in the anterior and lateral columns of the spinal cord. Intracellular TDP43 positive inclusions are usually present in the anterior horn cells of the spinal cord (Al-Chalabi et al., 2012, Arai et al., 2006, Brettschneider et al., 2013, Kato et al., 2000, Tan et al., 2007). In some genetic forms this is not the case, for example ALS caused by SOD1 mutations is TDP43 negative (Mackenzie, I. R. et al., 2007). C9ORF72 related ALS patients have p62 positive and TDP43 negative inclusions in the neurons of the cerebellum (Al-Sarraj et al., 2011).

2.5.4 Genetics

Approximately 5-10% of ALS is genetic. ALS is generally considered to be familial if there are two or more ALS patients in a family. Studies have revealed that 10% of apparently sporadic ALS has a

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genetic etiology (Kenna et al., 2013). Most mutations are inherited in an autosomal dominant pattern (Marangi, Traynor, 2015).

The C9ORF72 hexanucleotide repeat expansion mutation is the most common genetic cause of ALS in most Western populations, explaining about 27% of familial ALS and 3% of apparently sporadic ALS (Garcia-Redondo et al., 2013). As the C9ORF72 repeat expansion mutation is also the most common cause of genetic FTLD, it indicates a strong connection between the pathogenesis of these two diseases (Byrne et al., 2012).

The second most common cause of familial ALS are SOD1 mutations (Zou et al., 2017). SOD1 was the first gene whose mutations were found to cause ALS (Rosen, D. R. et al., 1993). Although most of them are inherited in an autosomal dominant manner, the recessive p.Asp91Ala mutation is more common among Finnish patients due to a founder effect (Andersen et al., 1995, Andersen et al., 1996). SOD1 encodes a cytoplasmic antioxidant enzyme superoxide dismutase-1 (Rosen, D. R.

et al., 1993). The enzyme works against oxygen toxicity by metabolizing superoxide radicals into molecular oxygen and hydrogen peroxide (Rosen, D. R. et al., 1993). SOD1 mutations have been considered to cause ALS by a toxic gain of function, although loss of function has also been proposed (Baskoylu et al., 2018).

There are several other genes whose mutations cause ALS (TABLE 4). As genetic studies of several genes in a gene panel test, and whole exome and genome sequencing have become available it has become apparent that some patients harbor mutations in multiple genes and ALS has an oligogenic inheritance pattern. It could explain the incomplete penetrance of many mutations such as the C9ORF72 hexanucleotide expansion mutation (Cooper-Knock et al., 2017, Giannoccaro et al., 2017, Pang et al., 2017)

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TABLE 4 Genes associated with ALS. Data from Marangi, Traynor, 2015 and original publications. GENE (HGNC) MIM#Genomic location (GRCh38) Inferitance patternClinical phenotypes (OMIM) Reference C9ORF726142609:27546545-27573865 ADFrontotemporal dementia and/or amyotrophic lateral sclerosis 1 (MIM 105550)

(Renton, Alan E et al., 2011, DeJesus-Hernandez et al., 2011) SOD1147450 21:31659692-31668930 AD, ARAmyotrophic lateral sclerosis 1 (MIM105400), Spastic tetraplegia and axial hypotonia, progressive (MIM618598) (Rosen, D. R. et al., 1993) SETX6084659:132261355-132356725 AD,AR

Amyotrophic lateral sclerosis 4, juvenile (MIM602433), Spinocerebellar ataxia, autosomal recessive, with axonal neuropathy 2 (MIM606002)

(Chen et al., 2004) SPG1161084415:44562695-44663677AR

Amyotrophic lateral sclerosis 5, juvenile (MIM602099), Charcot-Marie-Tooth disease, axonal, type 2X (MIM616668), Spastic paraplegia 11, autosomal recessive (MIM604360) (Orlacchio et al., 2010, Daoud et al., 2012) FUS13707016:31180109-31194870AD

Amyotrophic lateral sclerosis 6, with or without frontotemporal dementia (MIM608030), Essential tremor, hereditary, 4 (MIM614782)

(Vance et al., 2009, Kwiatkowski et al., 2009) VAPB60570420:58389210-58451100ADAmyotrophic lateral sclerosis 8 (MIM608627), Spinal muscular atrophy, late- onset, Finkel type (MIM182980)(Nishimura et al., 2004) ANG10585014:20684176-20694185ADAmyotrophic lateral sclerosis 9 (MIM611895) (Greenway et al., 2006) TARDBP605078 1:11012653-11030527 AD

Amyotrophic lateral sclerosis 10, with or without FTD (MIM612069), Frontotemporal lobar degeneration, TARDBP-related (MIM612069) (Gitcho et al., 2009, Kabashi et al., 2008, Sreedharan et al., 2008)

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FIG46093906:109691295-109825430 AD, AR Amyotrophic lateral sclerosis 11 (MIM612577), Polymicrogyria, bilateral temporooccipital(MIM612691), Charcot- Marie-Tooth disease, type 4J (MIM611228), Yunis-Varon syndrome (MIM216340)

(Chow, C. Y. et al., 2009) OPTN60243210:13100081-13138307AD

Amyotrophic lateral sclerosis 12 (MIM613435), Glaucoma 1, open angle, E(MIM137760), Glaucoma, normal tension, susceptibility to (MIM606657)

(Maruyama et al., 2010) VCP6010239:35056063-35072667 AD

Amyotrophic lateral sclerosis 14, with or without frontotemporal dementia (MIM613954), Charcot-Marie-Tooth disease, type 2Y(MIM616687), Inclusion body myopathy with early-onset Paget disease and frontotemporal dementia 1 (MIM167320)

(Johnson et al., 2010) UBQLN2300264X:56563592-56567009 XLDAmyotrophic lateral sclerosis 15, with or without frontotemporal dementia (MIM300857) (Deng et al., 2011) SIGMAR1601978 9:34634721-34637825ARAmyotrophic lateral sclerosis 16, juvenile (MIM614373), Spinal muscular atrophy, distal, autosomal recessive, 2 (MIM605726)

(Al-Saif, Al-Mohanna & Bohlega, 2011) CHMP2B6095123:87227308-87255555 ADAmyotrophic lateral sclerosis 17(MIM614696), Dementia, familial, nonspecific (MIM600795) (Parkinson et al., 2006) PFN117661017:4945651-4948529 ADAmyotrophic lateral sclerosis 18 (MIM614808) (Wu et al., 2012) MATR31640155:139273751-139331676 ADAmyotrophic lateral sclerosis 21 (MIM606070) (Johnson et al., 2014)

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CHCHD1061590322:23765833-23767971AD Frontotemporal dementia and/or amyotrophic lateral sclerosis 2 (MIM615911), Spinal muscular atrophy, Jokela type (MIM615048), Myopathy, isolated mitochondrial, autosomal dominant (MIM616209)

(Bannwarth et al., 2014, Chaussenot et al., 2014) SQSTM1601530 5:179806392-179838077AD, AR

Frontotemporal dementia and/or amyotrophic lateral sclerosis 3 (MIM616437), Myopathy, distal, with rimmed vacuoles (MIM617158), Neurodegeneration with ataxia, dystonia, and gaze palsy, childhood- onset(MIM617145), Paget disease of bone 3 (MIM167250)

(Fecto et al., 2011) TAF1560157417:35809483-35847241ADChondrosarcoma, extraskeletal myxoid (MIM612237) (Couthouis et al., 2011) EWSR113345022:29268253-29300522ADNeuroepithelioma (MIM612219), Ewing sarcoma (MIM612219) (Couthouis et al., 2012) HNRNPA116401712:54280725-54287086AD

Amyotrophic lateral sclerosis 20 (MIM615426), Inclusion body myopathy with early-onset Paget disease without frontotemporal dementia 3 (MIM615424)

(Kim et al., 2013) HNRNPA2B1 6001247:26189919-26200774 ADInclusion body myopathy with early-onset Paget disease with or without frontotemporal dementia (MIM615422) (Kim et al., 2013) SPAST6042772:32063550-32157636 ADSpastic paraplegia 4, autosomal dominant (MIM182601) (Meyer et al., 2005) PRPH17071012:49295143-49298697 AD,ARAmyotrophic lateral sclerosis, susceptibility to (MIM105400) (Leung et al., 2004)

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DCTN16011432:74361153-74392086 AD, AR Perry syndrome (MIM168605), Neuropathy, distal hereditary motor, type VIIB (MIM607641), Amyotrophic lateral sclerosis, susceptibility to (MIM105400)

(Puls et al., 2003) ERLIN26116058:37736626-37758421 ARSpastic paraplegia 18, autosomal recessive (MIM611225) (Al-Saif, Bohlega & Al- Mohanna, 2012) SS18L160647220:62,143,764-62,182,513AD NA (Chesi et al., 2013) DAO12405012:108880029-108901042 AD NA (Mitchell et al., 2010) PNPLA660319719:7534163-7561766 AR

Spastic paraplegia 39, autosomal recessive (MIM612020), Oliver-McFarlane syndrome (MIM275400), Boucher-Neuhauser syndrome (MIM215470), Laurence-Moon syndrome (MIM245800)

(Rainier et al., 2008) TUBA4A191110 2:219249709-219254607 ADAmyotrophic lateral sclerosis 22 with or without frontotemporal dementia (MIM616208) (Smith et al., 2014) KIF5A60282112:57550038-57586632AD

Spastic paraplegia 10, autosomal dominant (MIM604187), Myoclonus, intractable, neonatal (MIM617235), Amyotrophic lateral sclerosis, susceptibility to, 25 (MIM617921)

(Nicolas et al., 2018) NA: not in OMIM.

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Smoking has been concluded to be a risk factor for ALS based on several studies (Ingre et al., 2015). Physical activity has been concluded to be a minor risk factor in some studies although this has also been refuted (Chio et al., 2005, Pupillo et al., 2014). The association of several

autoimmune diseases and the development of ALS has also been studied (McCauley, Baloh, 2019).

It has been theorized that the pathogenesis of ALS is in some way relates to autoimmune diseases because ALS patients have been shown to have autoimmune diseases such as asthma more than the general population (Turner et al., 2013). However, standard immune suppression therapies have not shown to be effective in treating ALS patients (Baumann, 1965, Brown et al., 1986).

Microglial cells are the immune system cells in the nervous system and their dysfunction or abnormal activation has been suggested to be a factor in neuronal degeneration, for example microglial cells with wild type SOD1 have been shown to protect neurons with mutant SOD1 (Clement et al., 2003).

Glutamate excitotoxicity, which is caused by impaired glutamate intake by astrocytes, causes motor neuron damage in ALS (Bruijn et al., 1997). C9ORF72 mutations may cause altered RNA metabolism, along with SOD1 and TARDBP mutations (Alami et al., 2014, Lee et al., 2013, Gitcho et al., 2009). Altered RNA metabolism in turn causes among other things, altered protein translation and protein aggregates in motor neurons. The pathogenicity of this pathway is in part supported by the fact that most patients have protein aggregates in motor neurons (Mackenzie, I. R. et al., 2007, Da Cruz et al., 2017). SOD1 mutations also cause mitochondrial dysfunction and oxidative stress (Harraz et al., 2008). Impaired axonal transport has also been discovered (Williamson, Cleveland, 1999). The pathogenic pathways are presented in FIGURE 3.

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FIGURE 3 Pathogenic pathways in ALS. Modified from van den Bos et al., 2019.

C9orf72, TARDBP, FUS, SOD1

SOD1

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2.6 Next generation sequencing for novel pathogenic variant identification

Massive parallel sequencing (also known as second generation sequencing) is still widely known as next generation sequencing (NGS), although the technology has been in use for over a decade. The introduction of this sequencing method allowed sequencing of multiple genes simultaneously and ultimately the whole exome and genome can be sequenced at once as opposed to the previous method of Sanger sequencing one gene or exon of a gene at a time. This resulted in a massive leap in genetic research and diagnostics.

There are different variations in NGS technologies but all require library preparation done by fragmenting DNA and ligating adaptors with the fragments that enable the sequence to bind to a complementary counterpart (Metzker, 2010). The next step is to amplify the library using clonal amplification with PCR. The final step is the sequencing, which is usually done using a sequencing by synthesis method where the synthesis of amplified identical DNA strands produces light signals according to the different nucleotides (Metzker, 2010). As this method is more prone to errors the longer the sequences are, fragmentation of the DNA producing short reads is necessary. This need for DNA fragmentation generates its limitations in detecting certain types of genetic variation such as repeat expansion mutations, larger deletions and duplications, and complex

rearrangements(Goodwin, McPherson & McCombie, 2016). Although some of these limitations can be aided with bioinformatics, long read sequencing methods (also called third generation sequencing) are being developed rapidly to overcome the need to fragment DNA(Goodwin, McPherson & McCombie, 2016).

2.6.1 Whole exome sequencing

Whole exome sequencing is the sequencing of all the protein coding regions, exons, of genes. It has quickly become widely used in research and also as a diagnostic tool especially in pediatric syndromes(Trujillano et al., 2017). Although it is called whole exome sequencing it usually has challenges with adequate coverage of all exons and therefore the quality of sequencing and coverage of genes of special interest should be taken into consideration when analyzing the results.

2.6.2 Whole genome sequencing

Whole genome sequencing includes all the other areas of the genome in addition to the exome, meaning introns, noncoding areas and promoter areas(Lionel et al., 2018). The coverage of the exome is usually good and more stable in whole genome sequencing than in whole exome sequencing. It is also better at discovering larger deletions and duplications and other structural variants such as translocations(Lionel et al., 2018). However, the significantly larger amount of data compared to exome sequencing is a challenge for bioinformatics and variant interpretation.

As more genome sequencing data is added to population databases, knowledge of variation frequencies will help in interpreting the significance of intronic and other variants.

2.6.3 Variant classification

As sequencing methods have developed, the most challenging part of whole exome and genome sequencing is the data analysis and determining if the genetic variants are pathogenic and disease

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causing. The American College of Medical Genetics and Genomics (ACMG) and the Association for Molecular Pathology (AMP) have released a widely used guideline for variant classification of monogenic diseases (Richards et al., 2015). According to these criteria variants are classified as benign, probably benign, variant of unknown significance, probably pathogenic and pathogenic (Richards et al., 2015). One of the tools used in this classification are population databases with exome and genome sequencing data of apparently healthy individuals of which gnomAD and its predecessor with purely exome sequencing data ExAC, is the biggest and most widely used (Karczewski et al., 2019). The database includes data from different populations including over 10 000 Finnish samples, but is still lacking data from the populations of developing countries.

Many in silico tools have been developed to help predict a variant effect, especially for missense variants (Adzhubei et al., 2010, Kircher et al., 2014, Ng, Henikoff, 2003, Schwarz et al., 2014). Tools to help search previous literature such as the Human Gene Mutation Database (HGMD) have also been developed (Stenson et al., 2003). As genetic testing has become much more feasible and affordable, many novel variants are no longer reported in the literature. Therefore, easier ways to share results and seek to upload also unpublished information about discovered variants and their related phenotypes have been developed (Rehm et al., 2015).

One older tool that still holds its place is segregation analysis of the variant in a family, especially if the family is large with multiple affected and unaffected individuals who can participate. In the end, many missense variants still require functional studies to prove their pathogenicity.

Interpretation of the results of functional tests and their impact need to be careful as some are not as conclusive as others and guidelines to this have also been published recently (Brnich et al., 2019)

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3.AIMS OF THE STUDY

The general aim of this study was to investigate the genetic variation of patients with dementia disorders and ALS, and to combine this genetic information with information of the clinical and neuropathological phenotype.

The specific aims of this study were:

1. To identify the causative mutation and to comprehensively study the neuropathological phenotype in a Finnish family with FTLD (I)

2. To identify the causative mutation in a Finnish motor neuron disease patient and to study the frequency of this mutation and other genetic variants in the mutation carriers in a cohort of Finnish ALS patients (II)

3. To examine the genetics of vascular dementia in a cohort of Finnish vascular dementia patients (III)

4. To study the segregation and effect of a COL4A1/2 duplication in a Finnish family and to examine its frequency in a Finnish cohort of vascular dementia patients (IV)