The ability to objectively index dopamine (DA) levels in the brain has the potential to revolutionize the field of neuropsychopharmacology, as having a peripheral biomarker of brain DA would enable the objective monitoring of the progression of Parkinson's disease (PD) and other DA-dependent psychiatric states. Of particular relevance to commercialization, it would provide an objective measure of treatment efficacy. We used a DA-depletion approach to determine if peripheral D2Rs are a biomarker for brain DA; mainly, the 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) neurotoxin model and PD subjects, which are well-known models of DA depletion in the midbrain of rodents and humans, respectively. Dopamine depletion in the substantia nigra resulted a significant change to DA and norepinephrine (NE) levels in the plasma. Interestingly, these changes could be tracked as a time course from baseline to 15 days after injection with MPTP. Also, the proportion of D2R expressing leukocytes steadily increased (specifically B cells and T cells) during this same time of DA depletion. These results suggest that changes to the dopamine neuron population in the substantia nigra can be tracked with DA and NE level changes and D2R expression on B and T cells, providing a possible biomarker for nigral DA neuron loss to further investigate. In two cohorts of studies comparing subjects with PD vs controls, we found that Parkinson's subjects displayed significantly decreased D2R expression in all populations except for (natural killer) NK cells, CD16+ monocytes, and cytotoxic T cells. We also found that subjects with PD show increased levels in epinephrine (EPI) and DA as compared to control subjects. We did not, however, find any statistically significant correlations between the recorded leukocytic D2R downregulation in PD patients and their elevated DA and EPI plasma levels. Therefore, the results of this study did not provide a clear indication how brain DA levels are being represented in the periphery. Regardless, the modulation of peripheral D2Rs in PD and MPTP seen in this study do show that substantia nigra DA depletion in humans and rodents do manifest in the periphery. Although our study didn't result in a clear narrative of how nigral and peripheral DA system mirror each other, our result provide more evidence D2Rs may be both biomarkers and important substrates for treatment of DA-dependent disorders. Our results give a foundation from which future studies can investigate this connection further.

The full text of the thesis is currently restricted. / The full text will be available at the end of the embargo period: 1st Nov 2021

Genome-wide microarray technology has facilitated the systematic discovery of diagnostic biomarkers of cancers and other pathologies. However, meta-analyses of published arrays using melanoma as a test cancer has uncovered significant inconsistences that hinder advances in clinical practice. In this study a computational model for the integrated analysis of microarray datasets is proposed in order to provide a robust ranking of genes in terms of their relative significance; both genome-wide relative significance (GWRS) and genome-wide global significance (GWGS). When applied to five melanoma microarray datasets published between 2000 and 2011, a new 12-gene diagnostic biomarker signature for melanoma was defined (i.e., EGFR, FGFR2, FGFR3, IL8, PTPRF, TNC, CXCL13, COL11A1, CHP2, SHC4, PPP2R2C, and WNT4). Of these, CXCL13, COL11A1, PTPRF and SHC4 are components of the MAPK pathway and were validated by immunocyto- and immunohisto-chemistry. These proteins were found to be overexpressed in metastatic and primary melanoma cells in vitro and in melanoma tissue in situ compared to melanocytes cultured from healthy skin epidermis and normal healthy human skin. One challenge for the integrated analysis of microarray data is that the microarray data are produced using different platforms and bio-samples, e.g. including both cell line- and biopsy-based microarray datasets. In order to address these challenges, the computational model was further enhanced the stratification of datasets into either biopsy or cell line derived datasets, and via the weighting of microarray data based on quality criteria of data. The methods enhancement was applied to 14 microarray datasets of three cancers (breast, prostate, and melanoma) based on classification accuracy and on the capability to identify predictive biomarkers. Four novel measures for evaluating the capability to identify predictive biomarkers are proposed: (1) classifying independent testing data using wrapper feature selection with machine leaning, (2) assessing the number of common genes with the genes retrieved in independent testing data, (3) assessing the number of common genes with the genes retrieved in across multiple training datasets, (4) assessing the number of common genes with the genes validated in the literature. This enhancement of computational approach (i) achieved reliable classification performance across multiple datasets, (ii) recognized more significant genes into the top-ranked genes as compared to the genes detected by the independent test data, and (iii) detected more meaningful genes than were validated in previous melanoma studies in the literature.

Stroke is an acute neurological deficit that results from abnormal blood flow to the brain. The term stroke encompasses two primary subgroups: hemorrhagic stroke that is due to extravasation of blood and ischemic stroke that is due to vessel obstruction. Determining stroke type and underlying etiology is a crucial step in patient management as it influences treatment strategies. Currently diagnosis of stroke relies on clinical examination and neuroimaging, but there is a lack of rapid diagnostic and prognostic testing. Using microarray technology we identified a novel association between elevated peripheral blood expression of MCEMP1 and stroke. We have also shown that MCEMP1 discriminates between primary stroke types and predicts one-month post-stroke prognosis. Since genetic mechanisms underlying stroke remain incompletely understood we next conducted a global gene network analysis. Network analysis identified four large groups of co-expressed genes associated with ischemic stroke. NLRC4, CKLF, and HS.546375 were the most interconnected genes within unique modules and each was also independently associated with ischemic stroke. We show that multi-gene models have greater discriminative capacity for stroke and stroke prognosis, than single gene models. In addition to stroke biomarkers we also identified biomarkers of atrial fibrillation (AF), a known risk factor of stroke. Currently our understanding of the molecular mechanisms underlying AF remains incompletely understood. Thus we conducted whole blood expression profiling in patients with persistent AF before and after successful electrical cardioversion, a procedure that aims to restore sinus rhythm to the heart. We identified elevated expression of SLC25A20 and PDK4 during AF as compared with sinus rhythm. Furthermore we show that SLC25A20, PDK4 and NT-proBNP have incremental utility to discriminate AF from sinus rhythm. Taken together, the thesis implicates new genes with stroke and AF, and also indicates that whole blood RNA biomarkers may have clinical utility. / Thesis / Doctor of Philosophy (PhD)

Levels of circulating large extracellular vesicles (L-EVs) are increased in individuals with type 1 diabetes mellitus (T1DM) and associated with increased cardiovascular risk. T1DM in pregnancy induces vascular injury leading to adverse maternal and neonatal outcomes. Conversely, exercise has been shown to improve cardiovascular and metabolic health in pregnancy and may represent a non-pharmacological approach to improving pregnancy outcomes. Assessment of vascular health may aid in the identification of individuals at risk of complications and allow for intervention with strategies to improve the maternal vasculature. Unfortunately, there is a paucity of strategies for assessing vascular health in pregnant women. L-EVs are membrane-encapsulated particles released from stressed/injured cells. They are emerging biomarkers of vascular health. The purpose of this thesis was to assess the impact of T1DM and pregnancy on L-EV levels and protein composition, the relationship between L-EVs and pregnancy outcomes and the effect of exercise on L-EV levels. In aim #1, I observed that high levels of L-EVs are predictive of adverse pregnancy outcomes. In aim # 2, I examined the protein composition of circulating L-EVs in hypertensive, diabetic and healthy mice models. Diabetes-enriched proteins were involved in inflammation, SNARE signaling and NAD+ biogenesis. The changes were found in L-EV protein content were consistent with proteins associated with inflammation, cytoskeletal organization, and angiogenesis. Finally, in aim #3, I examined the changes in plasma L-EVs after an acute bout of moderate-intensity aerobic exercise in healthy pregnant and non-pregnant women. I observed that circulating L-EVs significantly decreased after the acute exercise only in non-pregnant individuals. Taken together, my thesis work advances knowledge on L-EVs in T1DM, pregnancy, and hypertension and sets the stage for future work on L-EVs as predictive biomarkers, for molecular profiling, and for monitoring of vascular health interventions in pregnancy.

BACKGROUND: The brain and retina are derived from the neuroectoderm and have structural and functional similarities. Researchers have separately analyzed brain and retinal perfusion in psychosis patients, but few studies have investigated the relationship between them. While the retina can serve as a proxy for brain disorders such as Alzheimer’s or Parkinson’s, less is known for psychosis. Thus, this study aims to examine the connection between retinal and brain perfusion in patients with psychosis. METHODS: A total of 48 participants, 17 healthy control and 31 probands, took part in the Bipolar and Schizophrenia Network on Intermediate Phenotype-2 (BSNIP-2) study at the Boston location at Beth Israel Deaconess Medical Center. Participants underwent arterial spin labeling MRI (magnetic resonance imaging) and retinal OCTA (optical coherence tomography angiography) imaging to determine brain and retinal perfusion, respectively. Whole retinal layer (superficial, deep, and choriocapillaris) and lobe-wise brain perfusion (frontal, temporal, parietal, occipital, and cingulate cortices) was used for analyses. Statistical analysis was performed in R and results were summarized using basic descriptive statistics. RESULTS: In probands, there was a significant positive correlation between vessel diameter index (VDI) and frontal lobe perfusion (r=0.74, p=0.000027) and between vessel diameter (VD) and frontal lobe perfusion (r=0.64, p=0.00077), but not for healthy controls. There was a significant negative correlation between VDI and temporal lobe perfusion (r=-0.56, p=0.0046), but not for healthy controls. There were no significant results for healthy controls or probands between retinal perfusion and occipital lobe perfusion. CONCLUSION: This study demonstrates that retinal perfusion may be a proxy marker for frontal lobe perfusion and could be used for predicting cognitive performance in a psychosis population given that the frontal lobe is primarily involved in executive functioning. There was an absence of a relationship between retinal perfusion and the occipital perfusion which suggests that retinal perfusion does not match visual neuronal pathway connections to the occipital cortex. These findings demonstrate a step towards appreciating how the retina can be leveraged to understand brain dysfunction in psychosis.

京都大学 / 新制・課程博士 / 博士(医学) / 甲第24993号 / 医博第5027号 / 新制||医||1069(附属図書館) / 京都大学大学院医学研究科医学専攻 / (主査)教授 滝田 順子, 教授 岩田 想, 教授 万代 昌紀 / 学位規則第4条第1項該当 / Doctor of Medical Science / Kyoto University / DFAM

Huntington disease (HD) is an inherited neurodegenerative disease caused by a trinucleotide repeat expansion in the huntingtin (HTT) gene. Metabolic dysfunction is a feature of HD that is recapitulated in HD mouse models. Our lab has shown that circadian feeding rhythms are disrupted in humanized HD mice and restored by suppression of brain HTT. Furthermore, when circadian feeding rhythm is artificially restored, in addition to normalization of metabolic function, liver and striatal HTT is temporarily reduced, demonstrating that HTT is involved in gut-brain feedback. The gut microbiome, which can regulate gut-brain feedback, has been implicated in the pathogenesis of other central nervous system disorders and we hypothesize it also plays a role in HD. The objective of this study is to investigate alterations in relative abundance of HD gut microbiota using existing plasma metabolomics data to identify candidate bacteria. If distinct microbiota profiles are demonstrated, this would provide the basis for future unbiased studies to investigate the complete HD microbiome.

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