Circulating plasma biomarkers of traumatic brain injury : Focus on the plasma levels of miR-124, miR-9, miR-136, and miR-434 as well as clusterin protein

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SHALINI DAS GUPTA

Circulating plasma biomarkers of traumatic brain injury

Dissertations in Health Sciences

PUBLICATIONS OF

THE UNIVERSITY OF EASTERN FINLAND

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CIRCULATING PLASMA BIOMARKERS OF TRAUMATIC BRAIN INJURY

FOCUS ON THE PLASMA LEVELS OF miR-124, miR-9, miR-136, AND miR-434 AS WELL AS CLUSTERIN PROTEIN

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Shalini Das Gupta

CIRCULATING PLASMA BIOMARKERS OF TRAUMATIC BRAIN INJURY

To be presented by permission of the

Faculty of Health Sciences, University of Eastern Finland for public examination in Medistudia auditorium MS300, Kuopio

on Wednesday, June 30^th 2021, at 12 o’clock noon

Publications of the University of Eastern Finland Dissertations in Health Sciences

No 628

A.I. Virtanen Institute for Molecular Sciences University of Eastern Finland, Kuopio

2021

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Shalini Das Gupta

CIRCULATING PLASMA BIOMARKERS OF TRAUMATIC BRAIN INJURY

To be presented by permission of the

Faculty of Health Sciences, University of Eastern Finland for public examination in Medistudia auditorium MS300, Kuopio

on Wednesday, June 30^th 2021, at 12 o’clock noon

Publications of the University of Eastern Finland Dissertations in Health Sciences

No 628

A.I. Virtanen Institute for Molecular Sciences University of Eastern Finland, Kuopio

2021

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Series Editors

Professor Tomi Laitinen, M.D., Ph.D.

Institute of Clinical Medicine, Clinical Physiology and Nuclear Medicine Faculty of Health Sciences

Professor Tarja Kvist, Ph.D.

Department of Nursing Science Faculty of Health Sciences Professor Ville Leinonen, M.D., Ph.D.

Institute of Clinical Medicine, Neurosurgery Faculty of Health Sciences

Professor Tarja Malm, Ph.D.

A.I. Virtanen Institute for Molecular Sciences Faculty of Health Sciences

Lecturer Veli-Pekka Ranta, Ph.D.

School of Pharmacy Faculty of Health Sciences

Distributor:

University of Eastern Finland Kuopio Campus Library

P.O.Box 1627 FI-70211 Kuopio, Finland

www.uef.fi/kirjasto Grano Oy, 2021

ISBN: 978-952-61-3802-2 (print/nid.) ISBN: 978-952-61-3803-9 (PDF)

ISSNL: 1798-5706 ISSN: 1798-5706 ISSN: 1798-5714 (PDF)

Author’s address: A.I.Virtanen Institute for Molecular Sciences University of Eastern Finland

KUOPIO FINLAND

Doctoral programme: Doctoral Programme in Molecular Medicine Supervisors: Professor Asla Pitkänen, M.D., Ph.D., D.Sc.

A.I.Virtanen Institute for Molecular Sciences University of Eastern Finland

KUOPIO FINLAND

Noora Puhakka, Ph.D.

KUOPIO FINLAND

Reviewers: Professor Iiris Hovatta, Ph.D.

Department of Psychology and Logopedics University of Helsinki

HELSINKI FINLAND

Professor R. Jeroen Pasterkamp, M.D., Ph.D.

Department of Translational Neuroscience University Medical Center Utrecht

UTRECHT

THE NETHERLANDS

Opponent: Professor David C. Henshall, Ph.D.

Department of Physiology & Medical Physics Royal College of Surgeons in Ireland

DUBLIN IRELAND

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Series Editors

Professor Tomi Laitinen, M.D., Ph.D.

Institute of Clinical Medicine, Clinical Physiology and Nuclear Medicine Faculty of Health Sciences

Professor Tarja Kvist, Ph.D.

Department of Nursing Science Faculty of Health Sciences Professor Ville Leinonen, M.D., Ph.D.

Institute of Clinical Medicine, Neurosurgery Faculty of Health Sciences

Professor Tarja Malm, Ph.D.

A.I. Virtanen Institute for Molecular Sciences Faculty of Health Sciences

Lecturer Veli-Pekka Ranta, Ph.D.

School of Pharmacy Faculty of Health Sciences

Distributor:

University of Eastern Finland Kuopio Campus Library

P.O.Box 1627 FI-70211 Kuopio, Finland

www.uef.fi/kirjasto Grano Oy, 2021

ISBN: 978-952-61-3802-2 (print/nid.) ISBN: 978-952-61-3803-9 (PDF)

ISSNL: 1798-5706 ISSN: 1798-5706 ISSN: 1798-5714 (PDF)

Author’s address: A.I.Virtanen Institute for Molecular Sciences University of Eastern Finland

KUOPIO FINLAND

Doctoral programme: Doctoral Programme in Molecular Medicine Supervisors: Professor Asla Pitkänen, M.D., Ph.D., D.Sc.

KUOPIO FINLAND

Noora Puhakka, Ph.D.

KUOPIO FINLAND

Reviewers: Professor Iiris Hovatta, Ph.D.

Department of Psychology and Logopedics University of Helsinki

HELSINKI FINLAND

Professor R. Jeroen Pasterkamp, M.D., Ph.D.

Department of Translational Neuroscience University Medical Center Utrecht

UTRECHT

THE NETHERLANDS

Opponent: Professor David C. Henshall, Ph.D.

Department of Physiology & Medical Physics Royal College of Surgeons in Ireland

DUBLIN IRELAND

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Das Gupta, Shalini

Circulating plasma biomarkers of traumatic brain injury. Focus on the plasma levels of miR-124, miR-9, miR-136, and miR-434 as well as clusterin protein Kuopio: University of Eastern Finland

Publications of the University of Eastern Finland Dissertations in Health Sciences 628. 2021, 101 p.

ISBN: 978-952-61-3802-2 (print) ISSNL: 1798-5706

ISSN: 1798-5706

ISBN: 978-952-61-3803-9 (PDF) ISSN: 1798-5714 (PDF)

ABSTRACT

Traumatic brain injury (TBI) refers to an injury to the brain caused by an external mechanical force. Each year, about 69 million people worldwide are affected by TBI.

However, due to the heterogeneity and complex pathophysiology of TBI, identifying sensitive and specific biomarkers, particularly for the difficult-to-diagnose mild TBI (mTBI) is challenging. Non-invasive blood-based biomarkers have the potential for TBI diagnosis, prognosis, clinical outcome prediction, and the identification of patients at risk of developing secondary pathologies. Animal models provide an excellent tool to advance biomarker research as they avoid several confounding factors and comorbidities associated with the patient population, thereby identifying markers specific to brain injury.

This thesis aims to identify circulating microRNA (miRNA) and protein biomarkers of TBI from the plasma of rats undergoing experimental lateral fluid percussion injury (FPI). It also aims to examine the translational potential of selected miRNA biomarkers in human TBI plasma. First, alteration in the plasma level of brain- enriched miR-124-3p was analysed at multiple timepoints after lateral FPI, and its relationship with cortical lesion size developed after injury was investigated. Next, a standardized protocol was designed to obtain haemolysis-free plasma for miRNA analysis. Since the identification of suitable endogenous controls for miRNA expression normalization is challenging, absolute quantification was performed in this protocol with the concentration-normalization approach. That is, for miRNA quantification, a fixed small RNA concentration rather than a fixed RNA volume was used. Following this standardized protocol, the plasma miRNA biomarkers of mTBI

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Das Gupta, Shalini

Circulating plasma biomarkers of traumatic brain injury. Focus on the plasma levels of miR-124, miR-9, miR-136, and miR-434 as well as clusterin protein Kuopio: University of Eastern Finland

Publications of the University of Eastern Finland Dissertations in Health Sciences 628. 2021, 101 p.

ISBN: 978-952-61-3802-2 (print) ISSNL: 1798-5706

ISSN: 1798-5706

ISBN: 978-952-61-3803-9 (PDF) ISSN: 1798-5714 (PDF)

ABSTRACT

Traumatic brain injury (TBI) refers to an injury to the brain caused by an external mechanical force. Each year, about 69 million people worldwide are affected by TBI.

However, due to the heterogeneity and complex pathophysiology of TBI, identifying sensitive and specific biomarkers, particularly for the difficult-to-diagnose mild TBI (mTBI) is challenging. Non-invasive blood-based biomarkers have the potential for TBI diagnosis, prognosis, clinical outcome prediction, and the identification of patients at risk of developing secondary pathologies. Animal models provide an excellent tool to advance biomarker research as they avoid several confounding factors and comorbidities associated with the patient population, thereby identifying markers specific to brain injury.

This thesis aims to identify circulating microRNA (miRNA) and protein biomarkers of TBI from the plasma of rats undergoing experimental lateral fluid percussion injury (FPI). It also aims to examine the translational potential of selected miRNA biomarkers in human TBI plasma. First, alteration in the plasma level of brain- enriched miR-124-3p was analysed at multiple timepoints after lateral FPI, and its relationship with cortical lesion size developed after injury was investigated. Next, a standardized protocol was designed to obtain haemolysis-free plasma for miRNA analysis. Since the identification of suitable endogenous controls for miRNA expression normalization is challenging, absolute quantification was performed in this protocol with the concentration-normalization approach. That is, for miRNA quantification, a fixed small RNA concentration rather than a fixed RNA volume was used. Following this standardized protocol, the plasma miRNA biomarkers of mTBI

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were investigated in the lateral FPI model as well as in human TBI patients.

Alteration in the plasma levels of these miRNAs with increase in injury severity was also examined. Finally, the post-TBI expression pattern of the clusterin protein in the brain and its biomarker potential in plasma were examined in the lateral FPI model.

Plasma miR-124-3p levels were elevated in rats at 2 d after TBI in comparison to sham-operated controls, and this elevation linearly associated with cortical lesion area developed at 2 mo after TBI. Spectrophotometric measurement detected that plasma aliquots pipetted farther away from the erythrocyte layer were least haemolysed and, therefore, most suitable for miRNA analysis. With small RNA concentration normalization, when RNA was extracted from different starting plasma volumes, similar miRNA copy numbers were obtained. In addition, compared to un-normalized samples, samples within one plasma volume group mostly exhibited a lower coefficient of variation (CV%) in the absolute miRNA concentration. This feature indicates that this normalization method can be implemented in the absence of suitable endogenous controls. At 2 d after TBI, elevated plasma miR-9a-3p, miR-136-3p, and miR-434-3p levels differentiated rats with mTBI from the naïve ones, with 100% sensitivity and specificity. Further, the plasma levels of these miRNAs increased with a corresponding increase in injury severity. A subpopulation of human mTBI patients also exhibited elevated miR-9-3p and miR-136-3p levels within 2 d after injury. The clusterin protein was elevated in the ipsilateral cortex, hippocampus, and thalamus of the rats with lateral FPI from 7 d-12 mo after injury, whereas plasma clusterin levels were downregulated at 2-6 h after TBI.

In conclusion, acutely altered plasma levels of miR-124-3p, miR-9a-3p, miR-136- 3p, and miR-434-3p, as well as clusterin protein were identified as novel biomarkers of TBI. miR-124-3p was a prognostic biomarker for chronic lesion severity. miR-9a- 3p, miR-136-3p, and miR-434-3p were biomarker candidates of mTBI and were sensitive to injury severity. Clusterin, a well-known risk factor for Alzheimer’s disease (AD), was also altered after TBI, indicating a plausible shared pathology between TBI and AD that needs further exploration.

Keywords: Biomarker, clusterin, lateral fluid percussion injury, microRNAs, miR- 124-3p, miR-9-3p, miR-136-3p, miR-434-3p, plasma, small RNA concentration- normalization, traumatic brain injury.

Das Gupta, Shalini

Veriplasmasta mitattavat mikroRNAt mir-124, mir-9 ja mir-434 sekä klusteriini- proteiini aivovamman biomarkkereina

Kuopio: Itä-Suomen yliopisto

Publications of the University of Eastern Finland Dissertations in Health Sciences 628. 2021, 101 s.

ISBN: 978-952-61-3802-2 (nid.) ISSNL: 1798-5706

ISSN: 1798-5706

ISBN: 978-952-61-3803-9 (PDF) ISSN: 1798-5714 (PDF)

TIIVISTELMÄ

Aivovamma aiheutuu päähän kohdistuneesta ulkoisesta mekaanisesta voimasta.

Maailmanlaajuisesti 69 miljoonaa ihmistä kärsii aivovammasta vuosittain. Taudin heterogeenisyyden ja monimutkaisen patofysiologian vuoksi toimivien biomarkkereiden löytäminen on haastavaa, etenkin vaikeasti diagnosoitavalle lievälle aivovammalle. Verestä mitattavat biomarkkerit edesauttavat ennusteen arvioinnissa, diagnostiikkavaiheessa ja lopullisen kliinisen oirekuvan arvioinnissa sekä edistävät sekundäärisille vaurioille alttiiden potilaiden tunnistusta. Eläinmallit tarjoavat erinomaisen työkalun biomarkkeritutkimuksen edistämiseksi, koska niiden avulla suljetaan pois useita potilasjoukkoihin liittyviä muuttujia ja liitännäissairauksia tunnistamalla täten aivovammalle ominaiset markkerit.

Tämän väitöskirjan tavoitteena on tunnistaa aivovammalle ominaisia verenkierrossa esiintyviä mikroRNA- ja proteiini-biomarkkereita rottien veriplasmasta nestepulssimallia käyttäen. Lisäksi tarkoituksena on tutkia esiintyvätkö valitut mikroRNA-biomarkkeriehdokkaat myös ihmisen veriplasmassa.

Aluksi tutkittiin aivoissa ilmentyvän miR-124-3p:n plasmapitoisuuden muutoksia useissa aikapisteissä kokeellisen aivovamman jälkeen, ja analysoitiin sen suhdetta kortikaalisen vaurion kokoon. Seuraavaksi suunniteltiin standardoitu menetelmä ei- hemolysoituneen veriplasman saamiseksi mikroRNA-analyysiä varten. Koska mikroRNA-pitoisuuden normalisointiin sopivien endogeenisten kontrollien identifioiminen on haastavaa, kvantitaatio suoritettiin konsentraatio- normalisointimenetelmällä. Toisin sanoen mikroRNA:n kvantitointiin käytettiin vakiona lyhytjaksoisten RNA-molekyylien pitoisuutta tilavuuden sijasta. Tällä

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were investigated in the lateral FPI model as well as in human TBI patients.

Alteration in the plasma levels of these miRNAs with increase in injury severity was also examined. Finally, the post-TBI expression pattern of the clusterin protein in the brain and its biomarker potential in plasma were examined in the lateral FPI model.

Plasma miR-124-3p levels were elevated in rats at 2 d after TBI in comparison to sham-operated controls, and this elevation linearly associated with cortical lesion area developed at 2 mo after TBI. Spectrophotometric measurement detected that plasma aliquots pipetted farther away from the erythrocyte layer were least haemolysed and, therefore, most suitable for miRNA analysis. With small RNA concentration normalization, when RNA was extracted from different starting plasma volumes, similar miRNA copy numbers were obtained. In addition, compared to un-normalized samples, samples within one plasma volume group mostly exhibited a lower coefficient of variation (CV%) in the absolute miRNA concentration. This feature indicates that this normalization method can be implemented in the absence of suitable endogenous controls. At 2 d after TBI, elevated plasma miR-9a-3p, miR-136-3p, and miR-434-3p levels differentiated rats with mTBI from the naïve ones, with 100% sensitivity and specificity. Further, the plasma levels of these miRNAs increased with a corresponding increase in injury severity. A subpopulation of human mTBI patients also exhibited elevated miR-9-3p and miR-136-3p levels within 2 d after injury. The clusterin protein was elevated in the ipsilateral cortex, hippocampus, and thalamus of the rats with lateral FPI from 7 d-12 mo after injury, whereas plasma clusterin levels were downregulated at 2-6 h after TBI.

In conclusion, acutely altered plasma levels of miR-124-3p, miR-9a-3p, miR-136- 3p, and miR-434-3p, as well as clusterin protein were identified as novel biomarkers of TBI. miR-124-3p was a prognostic biomarker for chronic lesion severity. miR-9a- 3p, miR-136-3p, and miR-434-3p were biomarker candidates of mTBI and were sensitive to injury severity. Clusterin, a well-known risk factor for Alzheimer’s disease (AD), was also altered after TBI, indicating a plausible shared pathology between TBI and AD that needs further exploration.

Keywords: Biomarker, clusterin, lateral fluid percussion injury, microRNAs, miR- 124-3p, miR-9-3p, miR-136-3p, miR-434-3p, plasma, small RNA concentration- normalization, traumatic brain injury.

Das Gupta, Shalini

Veriplasmasta mitattavat mikroRNAt mir-124, mir-9 ja mir-434 sekä klusteriini- proteiini aivovamman biomarkkereina

Kuopio: Itä-Suomen yliopisto

Publications of the University of Eastern Finland Dissertations in Health Sciences 628. 2021, 101 s.

ISBN: 978-952-61-3802-2 (nid.) ISSNL: 1798-5706

ISSN: 1798-5706

ISBN: 978-952-61-3803-9 (PDF) ISSN: 1798-5714 (PDF)

TIIVISTELMÄ

Aivovamma aiheutuu päähän kohdistuneesta ulkoisesta mekaanisesta voimasta.

Maailmanlaajuisesti 69 miljoonaa ihmistä kärsii aivovammasta vuosittain. Taudin heterogeenisyyden ja monimutkaisen patofysiologian vuoksi toimivien biomarkkereiden löytäminen on haastavaa, etenkin vaikeasti diagnosoitavalle lievälle aivovammalle. Verestä mitattavat biomarkkerit edesauttavat ennusteen arvioinnissa, diagnostiikkavaiheessa ja lopullisen kliinisen oirekuvan arvioinnissa sekä edistävät sekundäärisille vaurioille alttiiden potilaiden tunnistusta. Eläinmallit tarjoavat erinomaisen työkalun biomarkkeritutkimuksen edistämiseksi, koska niiden avulla suljetaan pois useita potilasjoukkoihin liittyviä muuttujia ja liitännäissairauksia tunnistamalla täten aivovammalle ominaiset markkerit.

Tämän väitöskirjan tavoitteena on tunnistaa aivovammalle ominaisia verenkierrossa esiintyviä mikroRNA- ja proteiini-biomarkkereita rottien veriplasmasta nestepulssimallia käyttäen. Lisäksi tarkoituksena on tutkia esiintyvätkö valitut mikroRNA-biomarkkeriehdokkaat myös ihmisen veriplasmassa.

Aluksi tutkittiin aivoissa ilmentyvän miR-124-3p:n plasmapitoisuuden muutoksia useissa aikapisteissä kokeellisen aivovamman jälkeen, ja analysoitiin sen suhdetta kortikaalisen vaurion kokoon. Seuraavaksi suunniteltiin standardoitu menetelmä ei- hemolysoituneen veriplasman saamiseksi mikroRNA-analyysiä varten. Koska mikroRNA-pitoisuuden normalisointiin sopivien endogeenisten kontrollien identifioiminen on haastavaa, kvantitaatio suoritettiin konsentraatio- normalisointimenetelmällä. Toisin sanoen mikroRNA:n kvantitointiin käytettiin vakiona lyhytjaksoisten RNA-molekyylien pitoisuutta tilavuuden sijasta. Tällä

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protokollalla ja käyttäen nestepulssimallia sekä aivovammapotilaiden veriplasmaa, tutkittiin mitkä verenkierrossa esiintyvät mikroRNAt voisivat toimia biomarkkereina lievälle aivovammalle. Lisäksi tutkittiin aivovamman vakavuuden ja mikroRNA- plasmapitoisuuksien yhteyttä. Lopuksi tutkittiin klusteriini-proteiinin ilmentymistä aivoissa aivovamman jälkeen ja sen potentiaalia toimia biomarkkerina.

Plasmasta mitatun miR-124-3p-pitoisuus oli koholla 2 vuorokautta kokeellisen aivovamman jälkeen, ja tämä kasvu korreloi kehittyneen kroonisen kortikaalisen vaurion koon kanssa. Spektrofotometrinen mittaus osoitti, että mitä kauempana erytrosyyttikerroksesta pipetoitu plasma oli, sitä vähemmän hemolysoitunut se oli ja siksi sopivin mikroRNA-analyysiin. Kun RNA eristettiin eri lähtöplasmatilavuuksista käyttäen lyhytjaksoisten RNA-molekyylien pitoisuutta normalisaatioon, tuloksena oli samankaltaiset mikroRNA-kopioluvut. Lisäksi verrattuna ei-normalisoituihin näytteisiin, myös variaatiokerroin oli pienempi, mikä osoittaa tämän normalisointimenetelmän käyttökelpoisuuden endogeenisten kontrollien puuttuessa. Plasmasta mitattujen miR-9a-3p-, miR-136-3p- ja miR-434- 3p-pitoisuuksien perusteella pystyttiin määrittämään kuuluiko rotta ryhmään, jolle oli aiheutettu aivovamma vai ryhmään, jolle ei ollut aiheutettu aivovammaa. Lisäksi näiden mikroRNA:iden plasmapitoisuudet nousivat vastaavasti aivovamman vakavuuden kasvaessa. Sama miR-9-3p:n ja miR-136-3p:n plasmapitoisuuden nousu pystyttiin näkemään myös osassa ihmisnäytteitä 2 päivää aivovamman jälkeen.

Klusteriini-proteiinin ilmentyminen oli lisääntynyt vaurioituneen aivopuoliskon aivokuorella, hippokampuksessa ja talamuksessa alkaen 7 päivän kohdalla kokeellisesta aivovammasta ja pysyen korkeana vielä 12 kuukauden päästä, kun taas plasman klusteriini-pitoisuus laski 2-6 tuntia aivovamman jälkeen.

Akuutisti muuttuneet miR-124-3p:n, miR-9a-3p:n, miR-136-3p:n ja miR-434-3p:n sekä klusteriini-proteiinin plasmapitoisuudet tunnistettiin aivovamman uusina biomarkkereina. Muuttuneen miR-124-3p:n plasmapitoisuuden perusteella voitiin ennustaa kehittyvän aivovaurion kokoa kun taas miR-9a-3p, miR-136-3p ja miR-434- 3p tunnistettiin lievän aivovamman biomarkkeriehdokkaiksi ollen herkkiä aivovamman vakavuudelle. Klusteriini-proteiinin, joka tunnetaan myös hyvin Alzheimerin taudin riskitekijänä, ilmentyminen muuttui aivovamman jälkeen, mikä viittaa linkkiin aivovamman ja Alzheimerin taudin välillä, mutta tämä tarvitsee vielä lisätutkimuksia.

Avainsanat: Aivovamma, biomarkkeri, klusteriini, mikroRNA, miR-124-3p, miR-9-3p, miR-136-3p, miR-434-3p, nestepulssimalli, normalisaatio perustuen lyhytjaksoisten RNA-molekyylien pitoisuuteen, plasma

In memory of my father-in-law

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protokollalla ja käyttäen nestepulssimallia sekä aivovammapotilaiden veriplasmaa, tutkittiin mitkä verenkierrossa esiintyvät mikroRNAt voisivat toimia biomarkkereina lievälle aivovammalle. Lisäksi tutkittiin aivovamman vakavuuden ja mikroRNA- plasmapitoisuuksien yhteyttä. Lopuksi tutkittiin klusteriini-proteiinin ilmentymistä aivoissa aivovamman jälkeen ja sen potentiaalia toimia biomarkkerina.

Plasmasta mitatun miR-124-3p-pitoisuus oli koholla 2 vuorokautta kokeellisen aivovamman jälkeen, ja tämä kasvu korreloi kehittyneen kroonisen kortikaalisen vaurion koon kanssa. Spektrofotometrinen mittaus osoitti, että mitä kauempana erytrosyyttikerroksesta pipetoitu plasma oli, sitä vähemmän hemolysoitunut se oli ja siksi sopivin mikroRNA-analyysiin. Kun RNA eristettiin eri lähtöplasmatilavuuksista käyttäen lyhytjaksoisten RNA-molekyylien pitoisuutta normalisaatioon, tuloksena oli samankaltaiset mikroRNA-kopioluvut. Lisäksi verrattuna ei-normalisoituihin näytteisiin, myös variaatiokerroin oli pienempi, mikä osoittaa tämän normalisointimenetelmän käyttökelpoisuuden endogeenisten kontrollien puuttuessa. Plasmasta mitattujen miR-9a-3p-, miR-136-3p- ja miR-434- 3p-pitoisuuksien perusteella pystyttiin määrittämään kuuluiko rotta ryhmään, jolle oli aiheutettu aivovamma vai ryhmään, jolle ei ollut aiheutettu aivovammaa. Lisäksi näiden mikroRNA:iden plasmapitoisuudet nousivat vastaavasti aivovamman vakavuuden kasvaessa. Sama miR-9-3p:n ja miR-136-3p:n plasmapitoisuuden nousu pystyttiin näkemään myös osassa ihmisnäytteitä 2 päivää aivovamman jälkeen.

Klusteriini-proteiinin ilmentyminen oli lisääntynyt vaurioituneen aivopuoliskon aivokuorella, hippokampuksessa ja talamuksessa alkaen 7 päivän kohdalla kokeellisesta aivovammasta ja pysyen korkeana vielä 12 kuukauden päästä, kun taas plasman klusteriini-pitoisuus laski 2-6 tuntia aivovamman jälkeen.

Akuutisti muuttuneet miR-124-3p:n, miR-9a-3p:n, miR-136-3p:n ja miR-434-3p:n sekä klusteriini-proteiinin plasmapitoisuudet tunnistettiin aivovamman uusina biomarkkereina. Muuttuneen miR-124-3p:n plasmapitoisuuden perusteella voitiin ennustaa kehittyvän aivovaurion kokoa kun taas miR-9a-3p, miR-136-3p ja miR-434- 3p tunnistettiin lievän aivovamman biomarkkeriehdokkaiksi ollen herkkiä aivovamman vakavuudelle. Klusteriini-proteiinin, joka tunnetaan myös hyvin Alzheimerin taudin riskitekijänä, ilmentyminen muuttui aivovamman jälkeen, mikä viittaa linkkiin aivovamman ja Alzheimerin taudin välillä, mutta tämä tarvitsee vielä lisätutkimuksia.

Avainsanat: Aivovamma, biomarkkeri, klusteriini, mikroRNA, miR-124-3p, miR-9-3p, miR-136-3p, miR-434-3p, nestepulssimalli, normalisaatio perustuen lyhytjaksoisten RNA-molekyylien pitoisuuteen, plasma

In memory of my father-in-law

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ACKNOWLEDGEMENTS

This work was carried out at the Epilepsy Research Laboratory at the A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland.

My sincere thanks go to my principal supervisor, Professor Asla Pitkänen, M.D., Ph.D., for providing me the opportunity to pursue my research in the field of neuroscience. Every session at the microscope with her was a new learning experience. She also taught me to observe my research findings from different perspectives and to develop new hypotheses from seemingly non-significant results, a skill that every researcher requires to progress in their research. I am also immensely grateful to my second supervisor, Noora Puhakka, Ph.D., for guiding me right from the days when I was a Master thesis student at the laboratory. From supervising my experiments in detail during my Master’s to providing me the independence of designing my experiments during the Ph.D., she has been an excellent mentor throughout.

My sincere gratitude to Professor Iiris Hovatta, Ph.D., and Professor R. Jeroen Pasterkamp, M.D., Ph.D., for acting as the Reviewers for this thesis. Your constructive comments significantly improved my book. I also wish to thank Professor David Henshall, Ph.D., for kindly accepting to be the opponent for this thesis. I am also grateful to Doctor Gerald Netto for patiently reviewing my thesis several times to revise the language.

I thank all my co-authors: Niina Vuokila, Riina Huusko, Jussi Tohka, Xavier Ekolle Ndode-Ekane, Robert Ciszek, Mette Heiskanen, Niina Lapinlampi, Janne Kukkonen, Ville Leinonen, Anssi Lipponen and Kaisa M.A. Paldanius for their significant contribution to the research presented in this thesis.

I am thankful to the UEF-AIVI personnel, especially Hanne Tanskanen, Jussi Keinänen, Joanna Huttunen, Asta Suhonen, Marja Järveläinen, Eleonora Tikkanen, Jari Nissinen and Ella Koistinen for continuously guiding me regarding several administrative issues during my entire Ph.D.

I wish to thank the former and present members of “EpiClub”: Anu Lipsanen, Tamuna Bolkvadze, Sofya Ziyatdinova, Diana Miszczuk, Francesco Noe', Jenni Karttunen, Mehwish Anwer, Amna Yasmin, Ying Wang, Vicente Navarro Ferrandis, Anssi Lipponen, Xavier Ekolle Ndode-Ekane, Jenni Kyyriäinen, Pedro Andrade, Tomi Paananen, Robert Ciszek, Niina Vuokila, Niina Lapinlampi, Mette Heiskanen, Natallie Kajevu, Johanna Hiltunen, Ivette Bañuelos-Cabrera, Leonardo Lara Valderrabano,

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ACKNOWLEDGEMENTS

This work was carried out at the Epilepsy Research Laboratory at the A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland.

My sincere thanks go to my principal supervisor, Professor Asla Pitkänen, M.D., Ph.D., for providing me the opportunity to pursue my research in the field of neuroscience. Every session at the microscope with her was a new learning experience. She also taught me to observe my research findings from different perspectives and to develop new hypotheses from seemingly non-significant results, a skill that every researcher requires to progress in their research. I am also immensely grateful to my second supervisor, Noora Puhakka, Ph.D., for guiding me right from the days when I was a Master thesis student at the laboratory. From supervising my experiments in detail during my Master’s to providing me the independence of designing my experiments during the Ph.D., she has been an excellent mentor throughout.

My sincere gratitude to Professor Iiris Hovatta, Ph.D., and Professor R. Jeroen Pasterkamp, M.D., Ph.D., for acting as the Reviewers for this thesis. Your constructive comments significantly improved my book. I also wish to thank Professor David Henshall, Ph.D., for kindly accepting to be the opponent for this thesis. I am also grateful to Doctor Gerald Netto for patiently reviewing my thesis several times to revise the language.

I thank all my co-authors: Niina Vuokila, Riina Huusko, Jussi Tohka, Xavier Ekolle Ndode-Ekane, Robert Ciszek, Mette Heiskanen, Niina Lapinlampi, Janne Kukkonen, Ville Leinonen, Anssi Lipponen and Kaisa M.A. Paldanius for their significant contribution to the research presented in this thesis.

I am thankful to the UEF-AIVI personnel, especially Hanne Tanskanen, Jussi Keinänen, Joanna Huttunen, Asta Suhonen, Marja Järveläinen, Eleonora Tikkanen, Jari Nissinen and Ella Koistinen for continuously guiding me regarding several administrative issues during my entire Ph.D.

I wish to thank the former and present members of “EpiClub”: Anu Lipsanen, Tamuna Bolkvadze, Sofya Ziyatdinova, Diana Miszczuk, Francesco Noe', Jenni Karttunen, Mehwish Anwer, Amna Yasmin, Ying Wang, Vicente Navarro Ferrandis, Anssi Lipponen, Xavier Ekolle Ndode-Ekane, Jenni Kyyriäinen, Pedro Andrade, Tomi Paananen, Robert Ciszek, Niina Vuokila, Niina Lapinlampi, Mette Heiskanen, Natallie Kajevu, Johanna Hiltunen, Ivette Bañuelos-Cabrera, Leonardo Lara Valderrabano,

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Elina Hämäläinen, Merja Lukkari and Jarmo Hartikainen. Thank you for making the life at the laboratory so friendly.

My special thanks go to Merja and Jarmo, as none of my experiments would have been possible without your help. In addition, I am grateful to Jenni Kyyriäinen, Niina Vuokila, and Mehwish Anwer for guiding me throughout the defense process. You were always ready to help whenever I had a question. Special thanks to Jenni for her help in writing the abstract of the thesis in Finnish. I also wish to thank Ivette, Leonardo, Mette, and Natallie for the wonderful trips that we took together. In addition, my heartfelt thanks to my Indian friends in Kuopio whose company always gave me the feeling of a home away from home.

I will always be grateful to my parents and my elder brother for their continuous guidance and support throughout my career. Thank you for believing in me and motivating me during the difficult days. Special thanks to my mother-in-law for always making my visit to the home in India during the holidays memorable. Thank you for understanding me, loving me, and respecting my career decisions. I am also indebted to my husband Subham, for his continuous love and support. You are the best companion that one can have. Thank you for patiently waiting for me to finish my studies and come back home. Last but not the least, my love goes to our nine- month-old puppy, Smiley. Thank you for choosing us to be your family. Your unconditional love makes me a better human.

This project was funded by the Center for International Mobility, Instrumentarium Foundation, Orion Research Foundation, Epilepsy Research Foundation, Maire Taponen Foundation, Doctoral Program in Molecular Medicine, Academy of Finland (Grants 272249, 273909, 317203 and 2285733-9), European Union’s Seventh Framework Program (FP7/2007-2013) under grant agreement n°602102 (EPITARGET), and National Institute of Neurological Disorders and Stroke (NINDS) Centres without Walls [grant number U54 NS100064].

Kuopio, May 11th, 2021 Shalini Das Gupta

LIST OF ORIGINAL PUBLICATIONS

This dissertation is based on the following original publications:

I Vuokila, N*., Gupta, S. D*., Huusko, R., Tohka, J., Puhakka, N., & Pitkänen, A.

Elevated acute plasma miR-124-3p level relates to evolution of larger cortical lesion area after traumatic brain injury. Neuroscience, 433 : 21-35, 2020.

II Gupta, S. D., Ndode-Ekane, X. E., Puhakka, N^#., & Pitkänen, A^#. Droplet digital polymerase chain reaction-based quantification of circulating microRNAs using small RNA concentration normalization. Scientific reports, 10(1): 1-16, 2020.

III Das Gupta, S., Ciszek, R., Heiskanen, M., Lapinlampi, N., Kukkonen, J., Leinonen, V., Puhakka, N^#., & Pitkänen, A^#.Plasma miR-9-3p and miR-136-3p as Potential Novel Diagnostic Biomarkers for Experimental and Human Mild Traumatic Brain Injury. International Journal of Molecular Sciences, 22(4): 1563, 2021.

IV Gupta, S. D., Lipponen, A., Paldanius, K. M., Puhakka, N., & Pitkänen, A.

Dynamics of clusterin protein expression in the brain and plasma following experimental traumatic brain injury. Scientific reports, 9(1): 1-12, 2019.

*These authors contributed equally to this work

# These authors jointly supervised this work

The publications were adapted with the permission of the copyright owners.

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Elina Hämäläinen, Merja Lukkari and Jarmo Hartikainen. Thank you for making the life at the laboratory so friendly.

My special thanks go to Merja and Jarmo, as none of my experiments would have been possible without your help. In addition, I am grateful to Jenni Kyyriäinen, Niina Vuokila, and Mehwish Anwer for guiding me throughout the defense process. You were always ready to help whenever I had a question. Special thanks to Jenni for her help in writing the abstract of the thesis in Finnish. I also wish to thank Ivette, Leonardo, Mette, and Natallie for the wonderful trips that we took together. In addition, my heartfelt thanks to my Indian friends in Kuopio whose company always gave me the feeling of a home away from home.

I will always be grateful to my parents and my elder brother for their continuous guidance and support throughout my career. Thank you for believing in me and motivating me during the difficult days. Special thanks to my mother-in-law for always making my visit to the home in India during the holidays memorable. Thank you for understanding me, loving me, and respecting my career decisions. I am also indebted to my husband Subham, for his continuous love and support. You are the best companion that one can have. Thank you for patiently waiting for me to finish my studies and come back home. Last but not the least, my love goes to our nine- month-old puppy, Smiley. Thank you for choosing us to be your family. Your unconditional love makes me a better human.

This project was funded by the Center for International Mobility, Instrumentarium Foundation, Orion Research Foundation, Epilepsy Research Foundation, Maire Taponen Foundation, Doctoral Program in Molecular Medicine, Academy of Finland (Grants 272249, 273909, 317203 and 2285733-9), European Union’s Seventh Framework Program (FP7/2007-2013) under grant agreement n°602102 (EPITARGET), and National Institute of Neurological Disorders and Stroke (NINDS) Centres without Walls [grant number U54 NS100064].

Kuopio, May 11th, 2021 Shalini Das Gupta

LIST OF ORIGINAL PUBLICATIONS

This dissertation is based on the following original publications:

I Vuokila, N*., Gupta, S. D*., Huusko, R., Tohka, J., Puhakka, N., & Pitkänen, A.

Elevated acute plasma miR-124-3p level relates to evolution of larger cortical lesion area after traumatic brain injury. Neuroscience, 433 : 21-35, 2020.

II Gupta, S. D., Ndode-Ekane, X. E., Puhakka, N^#., & Pitkänen, A^#. Droplet digital polymerase chain reaction-based quantification of circulating microRNAs using small RNA concentration normalization. Scientific reports, 10(1): 1-16, 2020.

III Das Gupta, S., Ciszek, R., Heiskanen, M., Lapinlampi, N., Kukkonen, J., Leinonen, V., Puhakka, N^#., & Pitkänen, A^#.Plasma miR-9-3p and miR-136-3p as Potential Novel Diagnostic Biomarkers for Experimental and Human Mild Traumatic Brain Injury. International Journal of Molecular Sciences, 22(4): 1563, 2021.

IV Gupta, S. D., Lipponen, A., Paldanius, K. M., Puhakka, N., & Pitkänen, A.

Dynamics of clusterin protein expression in the brain and plasma following experimental traumatic brain injury. Scientific reports, 9(1): 1-12, 2019.

*These authors contributed equally to this work

# These authors jointly supervised this work

The publications were adapted with the permission of the copyright owners.

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operated controls, in comparison to the naïve rats. ... 62 5.3.4 Elevation in plasma miR-9a-3p, miR-136-3p, and miR-434-3p levels was validated in rats with mTBI, in comparison to the naïve ones.63 5.3.5 Analysis in the whole animal cohort confirmed miR-9a-3p, miR-136- 3p, and miR-434-3p as mTBI biomarker candidates. ... 63 5.3.6 A subpopulation of human mTBI patients also exhibited elevated

plasma miR-9-3p and miR-136-3p levels. ... 64 5.4 Dynamics of clusterin protein expression after experimental lateral FPI (IV)

66

5.4.1 Punctate clusterin immunoreactivity was observed in the perilesional cortex, ipsilateral hippocampus, and thalamus of TBI rats. ... 66 5.4.2 Constitutive bilateral clusterin expression was observed in the

hypothalamus of the TBI and sham-operated control rats. ... 66 5.4.3 Clusterin immunoreactivity did not colocalize with neuronal, glial, or

mitochondrial markers. ... 67

5.4.4 Clusterin mRNA levels were elevated in the brain at 3 mo after TBI.

67

5.4.5 Plasma clusterin levels were acutely downregulated rather than chronically elevated. ... 68 6 DISCUSSION ... 69 6.1 Plasma miR-124-3p levels were acutely elevated in the rat model of lateral

FPI. ... 69 6.2 Standardization of rodent plasma miRNA biomarker analysis with the

absolute quantification of miRNA copies via the small RNA concentration- normalization method ... 72 6.3 Plasma miR-9-3p, miR-136-3p, and miR-434-3p levels at 2 d after TBI were

identified as biomarker candidates of mTBI in the lateral FPI model and in human patients. ... 76 6.4 Clusterin protein levels were elevated in the brain but not in plasma after

experimental lateral FPI. ... 79 7 CONCLUSIONS ... 83 REFERENCES ... 85

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5.1.3 Elevated acute plasma miR-124-3p levels linearly associated with the chronically developed cortical lesion area. ... 57 5.2 Absolute quantification of rodent plasma miRNA levels by using the small

RNA concentration-normalization method (II) ... 58 5.2.1 A higher proportion of haemolysis was observed in plasma aliquots

pipetted from the vicinity of the erythrocyte layer. ... 58 5.2.2 Qubit miRNA assay successfully measured plasma small RNA

concentrations extracted without carrier RNA. ... 59 5.2.3 Small RNA concentration normalization revealed similar miR-23a-3p

concentration in the 50-µl and 100-µl plasma volume groups. .... 59 5.2.4 Small RNA concentration normalization in the validation phase

revealed similar miR-103a-3p and miR-451a concentration in the 50- µl and 100-µl plasma volume groups. ... 60 5.2.5 The addition of the MS2 carrier RNA selectively improved miRNA

yield. ... 60 5.2.6 A-priori and a-posteriori normalizations revealed similar plasma

miRNA expression patterns. ... 61 5.3 Plasma miRNA expression profile in rats and in human patients with mTBI

(III) ... 61 5.3.1 Higher mortality and a longer duration of post-TBI apnoea was

observed in rats with sTBI in comparison to those with mTBI. ... 61 5.3.2 sRNA-Seq revealed 723 commonly expressed miRNAs across the four

animal groups. ... 62 5.3.3 Altered plasma miRNA levels were detected in TBI rats and in sham-

operated controls, in comparison to the naïve rats. ... 62 5.3.4 Elevation in plasma miR-9a-3p, miR-136-3p, and miR-434-3p levels was validated in rats with mTBI, in comparison to the naïve ones.63 5.3.5 Analysis in the whole animal cohort confirmed miR-9a-3p, miR-136- 3p, and miR-434-3p as mTBI biomarker candidates. ... 63 5.3.6 A subpopulation of human mTBI patients also exhibited elevated

plasma miR-9-3p and miR-136-3p levels. ... 64 5.4 Dynamics of clusterin protein expression after experimental lateral FPI (IV)

66

5.4.1 Punctate clusterin immunoreactivity was observed in the perilesional cortex, ipsilateral hippocampus, and thalamus of TBI rats. ... 66 5.4.2 Constitutive bilateral clusterin expression was observed in the

hypothalamus of the TBI and sham-operated control rats. ... 66 5.4.3 Clusterin immunoreactivity did not colocalize with neuronal, glial, or

mitochondrial markers. ... 67

5.4.4 Clusterin mRNA levels were elevated in the brain at 3 mo after TBI.

67

5.4.5 Plasma clusterin levels were acutely downregulated rather than chronically elevated. ... 68 6 DISCUSSION ... 69 6.1 Plasma miR-124-3p levels were acutely elevated in the rat model of lateral

FPI. ... 69 6.2 Standardization of rodent plasma miRNA biomarker analysis with the

absolute quantification of miRNA copies via the small RNA concentration- normalization method ... 72 6.3 Plasma miR-9-3p, miR-136-3p, and miR-434-3p levels at 2 d after TBI were

identified as biomarker candidates of mTBI in the lateral FPI model and in human patients. ... 76 6.4 Clusterin protein levels were elevated in the brain but not in plasma after

experimental lateral FPI. ... 79 7 CONCLUSIONS ... 83 REFERENCES ... 85

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ABBREVIATIONS

AD Alzheimer’s disease APOE Apolipoprotein E

AUC Area under the ROC curve BBB Blood-brain barrier

BEST Biomarkers, EndpointS, and other Tools

CA1 Cornu ammonis 1 region of the hippocampus

CD68 Cluster of Differentiation 68 cDNA Complementary DNA CNS Central nervous system Cq Cycle quantification CSF Cerebrospinal fluid

CT Computerized tomography CV Coefficient of variation

d Day

ddPCR Droplet digital polymerase chain reaction

DE Differentially expressed

∆G Gibbs free energy

EDTA Ethylenediaminetetraacetic acid

ELISA Enzyme-linked

immunosorbent assay FPI Fluid percussion injury GC-content Guanine-cytosine

content

GCS Glasgow coma scale GFAP Glial fibrillary acidic protein

h Hours

IF Immunofluorescence IHC Immunohistochemistry i.p Intraperitoneal

ir Immunoreactivity

LNA Locked nucleic acid

m1 Small RNA concentration measurement on day 1

mAb Monoclonal antibody MBP Myelin basic protein min Minute

miRNA MicroRNA

mo Month

MRI Magnetic resonance imaging mRNA messenger RNA

mTBI Mild traumatic brain injury

MTCO1 Mitochondrially encoded cytochrome C oxidase 1

ncRNA Non-coding RNA

NSE Neuron specific enolase pAB Polyclonal antibody

PCA Principal component analysis PCR Polymerase chain reaction PD Parkinson’s disease PFA Paraformaldehyde pre-miRNA Precursor miRNA pri-miRNA Primary miRNA PTE Post-traumatic epilepsy REMARK Reporting recommendations

for tumor marker prognostic studies

RISC RNA-induced silencing

complex

RNA Ribonucleic acid

ROC Receiver Operating

characteristic curve RT Reverse transcription

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ABBREVIATIONS

AD Alzheimer’s disease APOE Apolipoprotein E

AUC Area under the ROC curve BBB Blood-brain barrier

BEST Biomarkers, EndpointS, and other Tools

CA1 Cornu ammonis 1 region of the hippocampus

CD68 Cluster of Differentiation 68 cDNA Complementary DNA CNS Central nervous system Cq Cycle quantification CSF Cerebrospinal fluid

CT Computerized tomography CV Coefficient of variation

d Day

ddPCR Droplet digital polymerase chain reaction

DE Differentially expressed

∆G Gibbs free energy

EDTA Ethylenediaminetetraacetic acid

ELISA Enzyme-linked

immunosorbent assay FPI Fluid percussion injury GC-content Guanine-cytosine

content

GCS Glasgow coma scale GFAP Glial fibrillary acidic protein

h Hours

IF Immunofluorescence IHC Immunohistochemistry i.p Intraperitoneal

ir Immunoreactivity

LNA Locked nucleic acid

mAb Monoclonal antibody MBP Myelin basic protein min Minute

miRNA MicroRNA mo Month

MRI Magnetic resonance imaging mRNA messenger RNA

mTBI Mild traumatic brain injury

MTCO1 Mitochondrially encoded cytochrome C oxidase 1

ncRNA Non-coding RNA

NSE Neuron specific enolase pAB Polyclonal antibody

PCA Principal component analysis PCR Polymerase chain reaction PD Parkinson’s disease PFA Paraformaldehyde pre-miRNA Precursor miRNA pri-miRNA Primary miRNA PTE Post-traumatic epilepsy REMARK Reporting recommendations

for tumor marker prognostic studies

RISC RNA-induced silencing

complex

RNA Ribonucleic acid

ROC Receiver Operating

characteristic curve RT Reverse transcription

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RT-qPCR Reverse transcriptase quantitative polymerase chain reaction

S100B S100 calcium-binding protein B

SD Standard deviation

Simoa Single molecule array sRNA-Seq Small RNA sequencing sTBI Severe traumatic brain injury TBI Traumatic brain injury

UCH-L1 Ubiquitin carboxyl-terminal hydrolase isozyme L1

1 INTRODUCTION

Traumatic brain injury (TBI) is defined as “an alteration in brain function, or other evidence of brain pathology, caused by an external force” (Menon et al., 2010). TBI is predicted to be the third leading cause of global mortality and disability by 2020 (Neurotrauma, 2012). Each year, an estimated 69 million people worldwide suffer a TBI, with mild TBI (mTBI) accounting for approximately 80%-90% of those cases (Dewan et al., 2018). TBI is often characterized as a ‘silent epidemic’ as several cases remain unrecognized and excluded from official statistics (Rusnak, 2013).

Specifically, mTBI presents a diagnostic challenge as the majority of patients exhibit no visible structural damage to the brain detectable by current standard imaging methodologies, such as computerized tomography (CT), routinely available in trauma centres (Anzai and Minoshima, 2011). Further, most neuropsychiatric and neurodegenerative disabilities arising from less severe head trauma, for example, in mTBI, have a delayed onset and presentation (Kiraly and Kiraly, 2007). Overall, due to the heterogeneity of TBI and the limited understanding of its pathology, advances in TBI research have been slow (Edge, 2010).

According to the Biomarkers, EndpointS, and other Tools (BEST) resource developed by the Food and Drug Administration-National Institutes of Health Joint Leadership Council in 2016, a biomarker is defined as "a characteristic that is measured as an indicator of normal biological processes, pathogenic processes, or responses to an exposure or intervention, including therapeutic interventions”.

Biomarker can possess molecular, histologic, radiographic, and physiologic characteristics. Biomarker categories include diagnostic, prognostic, susceptibility/risk, predictive, response, monitoring, and safety biomarkers (Group, 2016). Identifying sensitive and specific biomarkers for TBI would allow an improved understanding of TBI pathophysiology and facilitate diagnosis, prognosis, and the development of novel therapeutics (Toman, Harrisson and Belli, 2016).

Cerebrospinal fluid (CSF) is a potentially attractive source for TBI biomarkers due to its proximity to the brain and involvement in central nervous system (CNS) functioning. However, blood-based biomarkers have gained significant interest as they are minimally invasive and cost-effective (Di Battista, Rhind and Baker, 2013).

Circulating protein biomarkers have demonstrated modest success in TBI diagnosis and prognosis (Kawata et al., 2016; Agoston, Shutes-David and Peskind, 2017; Dadas et al., 2018). In the past decade, circulating microRNAs (miRNAs) have emerged as potential biomarkers for TBI due to their stable expression in biofluids

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RT-qPCR Reverse transcriptase quantitative polymerase chain reaction

S100B S100 calcium-binding protein B

SD Standard deviation

Simoa Single molecule array sRNA-Seq Small RNA sequencing sTBI Severe traumatic brain injury TBI Traumatic brain injury

UCH-L1 Ubiquitin carboxyl-terminal hydrolase isozyme L1

1 INTRODUCTION

Traumatic brain injury (TBI) is defined as “an alteration in brain function, or other evidence of brain pathology, caused by an external force” (Menon et al., 2010). TBI is predicted to be the third leading cause of global mortality and disability by 2020 (Neurotrauma, 2012). Each year, an estimated 69 million people worldwide suffer a TBI, with mild TBI (mTBI) accounting for approximately 80%-90% of those cases (Dewan et al., 2018). TBI is often characterized as a ‘silent epidemic’ as several cases remain unrecognized and excluded from official statistics (Rusnak, 2013).

Specifically, mTBI presents a diagnostic challenge as the majority of patients exhibit no visible structural damage to the brain detectable by current standard imaging methodologies, such as computerized tomography (CT), routinely available in trauma centres (Anzai and Minoshima, 2011). Further, most neuropsychiatric and neurodegenerative disabilities arising from less severe head trauma, for example, in mTBI, have a delayed onset and presentation (Kiraly and Kiraly, 2007). Overall, due to the heterogeneity of TBI and the limited understanding of its pathology, advances in TBI research have been slow (Edge, 2010).

According to the Biomarkers, EndpointS, and other Tools (BEST) resource developed by the Food and Drug Administration-National Institutes of Health Joint Leadership Council in 2016, a biomarker is defined as "a characteristic that is measured as an indicator of normal biological processes, pathogenic processes, or responses to an exposure or intervention, including therapeutic interventions”.

Biomarker can possess molecular, histologic, radiographic, and physiologic characteristics. Biomarker categories include diagnostic, prognostic, susceptibility/risk, predictive, response, monitoring, and safety biomarkers (Group, 2016). Identifying sensitive and specific biomarkers for TBI would allow an improved understanding of TBI pathophysiology and facilitate diagnosis, prognosis, and the development of novel therapeutics (Toman, Harrisson and Belli, 2016).

Cerebrospinal fluid (CSF) is a potentially attractive source for TBI biomarkers due to its proximity to the brain and involvement in central nervous system (CNS) functioning. However, blood-based biomarkers have gained significant interest as they are minimally invasive and cost-effective (Di Battista, Rhind and Baker, 2013).

Circulating protein biomarkers have demonstrated modest success in TBI diagnosis and prognosis (Kawata et al., 2016; Agoston, Shutes-David and Peskind, 2017; Dadas et al., 2018). In the past decade, circulating microRNAs (miRNAs) have emerged as potential biomarkers for TBI due to their stable expression in biofluids

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(Mitchell et al., 2008; Martinez and Peplow, 2017; Di Pietro, Yakoub, et al., 2018; Atif and Hicks, 2019; Toffolo et al., 2019). Circulating miRNAs are resistant to enzymatic degradation, repeated freeze-thaw cycles, and extreme pH conditions, a feature which gives them an advantage over protein biomarkers (Balakathiresan et al., 2015). However, most studies have investigated miRNAs as biomarkers of TBI in human patients, with merely some overlap in the biomarker signature obtained across these studies (Atif and Hicks, 2019). In this regard, experimental animal models can significantly advance biomarker identification as they avoid confounding factors and comorbidities that introduce heterogeneity in the TBI patient population (Agoston, Shutes-David and Peskind, 2017). Further, animal models provide an excellent tool to harmonize the pre-analytical and technical factors involved in circulating biomarker quantification, facilitating reproducible translation to the clinic (Kamnaksh et al., 2019).

This study aims to identify novel circulating miRNA and protein biomarkers of TBI, in adult male Sprague-Dawley rats by using the experimental lateral fluid percussion injury (FPI) model and in human TBI patient samples. In the first study, the temporal expression profile of brain-enriched miR-124-3p was analysed in the plasma of rats at both acute and chronic timepoints after TBI. Further, the prognostic potential of altered plasma miR-124-3p levels at an acute timepoint after TBI for chronic brain lesion severity was investigated. In the second study, a standardized protocol was designed to perform the absolute quantification of plasma miRNA copy number based on small RNA concentration normalization from non-haemolysed rat tail-vein plasma via droplet digital polymerase chain reaction (ddPCR). This protocol was an advancement over our previously published pipeline for plasma miRNA biomarker analysis (van Vliet et al., 2017). In the third study, high- throughput small RNA-Sequencing (sRNA-Seq) was performed from the plasma of rats at 2 d after TBI to identify miRNA biomarkers of mTBI. These miRNA biomarker candidates were then selected for analysis in the plasma of human patients with mTBI and severe TBI (sTBI). The impact of varying injury severity on plasma miRNA levels was also investigated in this study. Finally, the expression pattern of the clusterin protein in the brain and plasma was investigated at both acute and chronic timepoints after TBI, to investigate its biomarker potential in the lateral FPI model in rats.

2 REVIEW OF THE LITERATURE

2.1 TRAUMATIC BRAIN INJURY

TBI can result from a blunt blow to the head, the penetration of the skull, acceleration or deceleration injury, or blast exposure (Dixon, 2017). TBI is a global health problem (Maas et al., 2017; Dewan et al., 2018). About half of the world’s population will suffer from at least one TBI in their lifetime (Maas et al., 2017). The burden is more prominent in the younger population in low- and middle-income countries, where road traffic accidents account for the greatest proportion of TBI incidence. In high-income countries, the elderly population is more affected, the major cause of TBI being falls (Roozenbeek, Maas and Menon, 2013; Maas et al., 2017; Dewan et al., 2018). In 2018, an overall TBI incidence rate of 1299 cases per 100,000 people was identified in North America; it was 1012 cases in Europe (Dewan et al., 2018). TBI is a disease process in continuum rather than a single event, with lifelong effects on morbidity and mortality (Masel and DeWitt, 2010). It is a major risk factor for post-traumatic epilepsy (PTE), the 30-year cumulative incidence of which is 2.1% for mild injuries, 4.2% for moderate, and 16.7% for severe ones (Annegers and Coan, 2000; Pitkänen and Immonen, 2014). TBI also increases susceptibility to sleep disorders, Alzheimer’s disease (AD), Parkinson’s disease (PD), post-TBI hypopituitarism, stroke, psychiatric disorders, as well as non-neurological sexual, musculoskeletal, and metabolic dysfunctions (Masel and DeWitt, 2010;

Bramlett and Dietrich, 2015; Wilson et al., 2017). Repeated mTBI in athletes and military personnel poses a high risk of developing chronic traumatic encephalopathy (Baugh et al., 2012).

2.1.1 Pathophysiology of TBI

TBI has a complex pathophysiology involving both acute and chronic damages to the brain (Figure 1, (Mohamadpour, Whitney and Bergold, 2019)). The primary damage is inflicted on the brain immediately at the moment of injury, producing mechanical tissue damage and disrupting normal brain functioning. Primary damage involves skull fractures and contusion, as well as the development of intracranial haematoma, cerebrovascular damage, and diffuse axonal injury (Ray, Dixon and Banik, 2002; Werner and Engelhard, 2007; Kaur and Sharma, 2018). The primary damage immediately triggers a secondary injury that evolves for weeks to

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(Mitchell et al., 2008; Martinez and Peplow, 2017; Di Pietro, Yakoub, et al., 2018; Atif and Hicks, 2019; Toffolo et al., 2019). Circulating miRNAs are resistant to enzymatic degradation, repeated freeze-thaw cycles, and extreme pH conditions, a feature which gives them an advantage over protein biomarkers (Balakathiresan et al., 2015). However, most studies have investigated miRNAs as biomarkers of TBI in human patients, with merely some overlap in the biomarker signature obtained across these studies (Atif and Hicks, 2019). In this regard, experimental animal models can significantly advance biomarker identification as they avoid confounding factors and comorbidities that introduce heterogeneity in the TBI patient population (Agoston, Shutes-David and Peskind, 2017). Further, animal models provide an excellent tool to harmonize the pre-analytical and technical factors involved in circulating biomarker quantification, facilitating reproducible translation to the clinic (Kamnaksh et al., 2019).

This study aims to identify novel circulating miRNA and protein biomarkers of TBI, in adult male Sprague-Dawley rats by using the experimental lateral fluid percussion injury (FPI) model and in human TBI patient samples. In the first study, the temporal expression profile of brain-enriched miR-124-3p was analysed in the plasma of rats at both acute and chronic timepoints after TBI. Further, the prognostic potential of altered plasma miR-124-3p levels at an acute timepoint after TBI for chronic brain lesion severity was investigated. In the second study, a standardized protocol was designed to perform the absolute quantification of plasma miRNA copy number based on small RNA concentration normalization from non-haemolysed rat tail-vein plasma via droplet digital polymerase chain reaction (ddPCR). This protocol was an advancement over our previously published pipeline for plasma miRNA biomarker analysis (van Vliet et al., 2017). In the third study, high- throughput small RNA-Sequencing (sRNA-Seq) was performed from the plasma of rats at 2 d after TBI to identify miRNA biomarkers of mTBI. These miRNA biomarker candidates were then selected for analysis in the plasma of human patients with mTBI and severe TBI (sTBI). The impact of varying injury severity on plasma miRNA levels was also investigated in this study. Finally, the expression pattern of the clusterin protein in the brain and plasma was investigated at both acute and chronic timepoints after TBI, to investigate its biomarker potential in the lateral FPI model in rats.

2 REVIEW OF THE LITERATURE

2.1 TRAUMATIC BRAIN INJURY

TBI can result from a blunt blow to the head, the penetration of the skull, acceleration or deceleration injury, or blast exposure (Dixon, 2017). TBI is a global health problem (Maas et al., 2017; Dewan et al., 2018). About half of the world’s population will suffer from at least one TBI in their lifetime (Maas et al., 2017). The burden is more prominent in the younger population in low- and middle-income countries, where road traffic accidents account for the greatest proportion of TBI incidence. In high-income countries, the elderly population is more affected, the major cause of TBI being falls (Roozenbeek, Maas and Menon, 2013; Maas et al., 2017; Dewan et al., 2018). In 2018, an overall TBI incidence rate of 1299 cases per 100,000 people was identified in North America; it was 1012 cases in Europe (Dewan et al., 2018). TBI is a disease process in continuum rather than a single event, with lifelong effects on morbidity and mortality (Masel and DeWitt, 2010). It is a major risk factor for post-traumatic epilepsy (PTE), the 30-year cumulative incidence of which is 2.1% for mild injuries, 4.2% for moderate, and 16.7% for severe ones (Annegers and Coan, 2000; Pitkänen and Immonen, 2014). TBI also increases susceptibility to sleep disorders, Alzheimer’s disease (AD), Parkinson’s disease (PD), post-TBI hypopituitarism, stroke, psychiatric disorders, as well as non-neurological sexual, musculoskeletal, and metabolic dysfunctions (Masel and DeWitt, 2010;

Bramlett and Dietrich, 2015; Wilson et al., 2017). Repeated mTBI in athletes and military personnel poses a high risk of developing chronic traumatic encephalopathy (Baugh et al., 2012).

2.1.1 Pathophysiology of TBI

TBI has a complex pathophysiology involving both acute and chronic damages to the brain (Figure 1, (Mohamadpour, Whitney and Bergold, 2019)). The primary damage is inflicted on the brain immediately at the moment of injury, producing mechanical tissue damage and disrupting normal brain functioning. Primary damage involves skull fractures and contusion, as well as the development of intracranial haematoma, cerebrovascular damage, and diffuse axonal injury (Ray, Dixon and Banik, 2002; Werner and Engelhard, 2007; Kaur and Sharma, 2018). The primary damage immediately triggers a secondary injury that evolves for weeks to

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months after injury (Dixon, 2017). Secondary brain injury involves a cascade of molecular events, including cerebral ischaemia, increase in intracranial pressure, excitotoxicity, blood-brain barrier (BBB) damage, mitochondrial dysfunction, oxidative stress, and neuroinflammation (Ray, Dixon and Banik, 2002; Werner and Engelhard, 2007; Pitkänen and Lukasiuk, 2009; Kaur and Sharma, 2018). Identifying a therapeutic window for TBI is thus challenging, but early intervention may block at least some secondary injury mechanisms and produce long-lasting therapeutic effects (Mohamadpour, Whitney and Bergold, 2019).

Figure 1. Primary and secondary injury mechanisms following traumatic brain injury.

2.1.2 Diagnosis of TBI

TBI diagnosis involves the assessment of injury severity with the 15-point Glasgow coma scale (GCS) score (Teasdale and Jennett, 1974) and the duration of loss of consciousness and post-traumatic amnesia (Levin and Diaz-Arrastia, 2015). Based on the severity, TBI is classified as mild (GCS score 13-15), moderate (GCS score 9- 12), or severe (GCS score <8) (Ling, Marshall and Moore, 2010). Neuroimaging is performed to detect intracranial injuries in patients with suspected TBI (Lee and Newberg, 2005). A CT scan is usually performed to visualize cerebral pathology, within 24 h of injury. Magnetic resonance imaging (MRI) provides a more sensitive and accurate assessment of neuronal damage, at 48-72 h after injury (Lee and Newberg, 2005). However, currently available diagnostic modalities often result in

under-diagnosis, specifically in patients with mTBI (Cassidy et al., 2004). Most mTBI patients recover relatively fast, but almost 30% experience chronic neurobehavioural deficits (Levin and Diaz-Arrastia, 2015). mTBI diagnosis remains complicated due to several factors. First, patients typically present with no detectable damage in a CT or MRI examination. Second, the early identification of patients who will eventually develop chronic symptoms is difficult. Third, outcome assessments traditionally used for moderately to severely injured patients inadequately capture the subtle neurobehavioural deficits in mTBI. Finally, the chronic symptoms of mTBI often overlap with those in patients with other neuropathologies unrelated to TBI (Lee and Newberg, 2005; Mondello et al., 2014;

Levin and Diaz-Arrastia, 2015).

2.1.3 Need for TBI biomarkers

According to the Bakay and Ward’s criteria, the most important characteristics that brain injury biomarkers should possess include high specificity and sensitivity for brain tissue injury, rapid release to the circulation and availability of reliable assays for their immediate quantification (Table 1). Biomarkers in TBI can assist in detecting concussion, predicting negative and positive head CT findings, and predicting outcome for different TBI severities. They provide objective and quantitative information regarding the underlying ongoing pathophysiologic mechanisms that lead to the neurologic deficits observed after TBI (Gan et al., 2019).

Biomarkers facilitate the characterization and categorization of TBI in individuals (Mondello et al., 2014). Prognostic biomarkers identifying patients at risk of developing secondary pathologies after TBI can help provide individualised patient management and care (Hergenroeder et al., 2008). Further, biomarkers correlating with disease progression and long-term outcome can serve as surrogate markers in clinical trials (Katz, 2004; Hergenroeder et al., 2008). However, given the complex and dynamic nature of TBI pathophysiology, the long-term longitudinal measurement and identification of a combination of biomarkers is required to achieve clinically relevant diagnostic accuracy (Hergenroeder et al., 2008; Martinez and Stabenfeldt, 2019).

Circulating plasma biomarkers of traumatic brain injury : Focus on the plasma levels of miR-124, miR-9, miR-136, and miR-434 as well as clusterin protein

SHALINI DAS GUPTA

Circulating plasma biomarkers of traumatic brain injury

Dissertations in Health Sciences

CIRCULATING PLASMA BIOMARKERS OF TRAUMATIC BRAIN INJURY

Shalini Das Gupta

CIRCULATING PLASMA BIOMARKERS OF TRAUMATIC BRAIN INJURY

Shalini Das Gupta

CIRCULATING PLASMA BIOMARKERS OF TRAUMATIC BRAIN INJURY

ABSTRACT

ABSTRACT

TIIVISTELMÄ

TIIVISTELMÄ

ACKNOWLEDGEMENTS

ACKNOWLEDGEMENTS

LIST OF ORIGINAL PUBLICATIONS

LIST OF ORIGINAL PUBLICATIONS

CONTENTS

CONTENTS

ABBREVIATIONS

ABBREVIATIONS

1 INTRODUCTION

1 INTRODUCTION

2 REVIEW OF THE LITERATURE

2.1 TRAUMATIC BRAIN INJURY

2 REVIEW OF THE LITERATURE

2.1 TRAUMATIC BRAIN INJURY