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Item Automated Evaluation of Neurological Disorders Through Electronic Health Record Analysis(2024-08) Prince, Md Rakibul Islam; Ben Miled, Zina; El-Sharkawy, Mohamed A.; Zhang, QingxueNeurological disorders present a considerable challenge due to their variety and diagnostic complexity especially for older adults. Early prediction of the onset and ongoing assessment of the severity of these disease conditions can allow timely interventions. Currently, most of the assessment tools are time-consuming, costly, and not suitable for use in primary care. To reduce this burden, the present thesis introduces passive digital markers for different disease conditions that can effectively automate the severity assessment and risk prediction from different modalities of electronic health records (EHR). The focus of the first phase of the present study in on developing passive digital markers for the functional assessment of patients suffering from Bipolar disorder and Schizophrenia. The second phase of the study explores different architectures for passive digital markers that can predict patients at risk for dementia. The functional severity PDM uses only a single EHR modality, namely medical notes in order to assess the severity of the functioning of schizophrenia, bipolar type I, or mixed bipolar patients. In this case, the input of is a single medical note from the electronic medical record of the patient. This note is submitted to a hierarchical BERT model which classifies at-risk patients. A hierarchical attention mechanism is adopted because medical notes can exceed the maximum allowed number of tokens by most language models including BERT. The functional severity PDM follows three steps. First, a sentence-level embedding is produced for each sentence in the note using a token-level attention mechanism. Second, an embedding for the entire note is constructed using a sentence-level attention mechanism. Third, the final embedding is classified using a feed-forward neural network which estimates the impairment level of the patient. When used prior to the onset of the disease, this PDM is able to differentiate between severe and moderate functioning levels with an AUC of 76%. Disease-specific severity assessment PDMs are only applicable after the onset of the disease and have AUCs of nearly 85% for schizophrenia and bipolar patients. The dementia risk prediction PDM considers multiple EHR modalities including socio-demographic data, diagnosis codes and medical notes. Moreover, the observation period and prediction horizon are varied for a better understanding of the practical limitations of the model. This PDM is able to identify patients at risk of dementia with AUCs ranging from 70% to 92% as the observation period approaches the index date. The present study introduces methodologies for the automation of important clinical outcomes such as the assessment of the general functioning of psychiatric patients and the prediction of risk for dementia using only routine care data.Item Characteristics of Bipolar I patients grouped by externalizing disorders(Elsevier, 2015-06-01) Swaminathan, Shanker; Koller, Daniel L.; Foroud, Tatiana; Edenberg, Howard J.; Xuei, Xiaoling; Niculescu, Alexander B.; Bipolar Genome Study (BiGS) Consortium; Nurnberger, John I.; Department of Psychiatry, IU School of MedicineBACKGROUND: Bipolar disorder co-occurs with a number of disorders with externalizing features. The aim of this study is to determine whether Bipolar I (BPI) subjects with comorbid externalizing disorders and a subgroup with externalizing symptoms prior to age 15 have different clinical features than those without externalizing disorders and whether these could be attributed to specific genetic variations. METHODS: A large cohort (N=2505) of Bipolar I subjects was analyzed. Course of illness parameters were compared between an Externalizing Group, an Early-Onset Subgroup and a Non-Externalizing Group in the Discovery sample (N=1268). Findings were validated using an independent set of 1237 BPI subjects (Validation sample). Genetic analyses were carried out. RESULTS: Subjects in the Externalizing Group (and Early-Onset Subgroup) tended to have a more severe clinical course, even in areas specifically related to mood disorder such as cycling frequency and rapid mood switching. Regression analysis showed that the differences are not completely explainable by substance use. Genetic analyses identified nominally associated SNPs; calcium channel genes were not enriched in the gene variants identified. LIMITATIONS: Validation in independent samples is needed to confirm the genetic findings in the present study. CONCLUSIONS: Our findings support the presence of an externalizing disorder subphenotype within BPI with greater severity of mood disorder and possible specific genetic features.Item Differential responses to lithium in hyperexcitable neurons from patients with bipolar disorder.(NPG, 2015-11-05) Mertens, Jerome; Wang, Qiu-Wen; Kim, Yongsung; Yu, Diana X.; Pham, Son; Yang, Bo; Zheng, Yi; Diffenderfer, Kenneth E.; Zhang, Jian; Soltani, Sheila; Eames, Tameji; Schafer, Simon T.; Boyer, Leah; Marchetto, Maria C.; Nurnberger, John I.; Calabrese, Joseph R.; Oedegaard, Ketil J.; McCarthy, Michael J.; Zandi, Peter P.; Alda, Martin; Nievergelt, Caroline M.; Mi, Shuangli; Brennand, Kristen J.; Kelsoe, John R.; Gage, Fred H.; Yao, Jun; Department of Psychiatry, IU School of MedicineBipolar disorder is a complex neuropsychiatric disorder that is characterized by intermittent episodes of mania and depression; without treatment, 15% of patients commit suicide. Hence, it has been ranked by the World Health Organization as a top disorder of morbidity and lost productivity. Previous neuropathological studies have revealed a series of alterations in the brains of patients with bipolar disorder or animal models, such as reduced glial cell number in the prefrontal cortex of patients, upregulated activities of the protein kinase A and C pathways and changes in neurotransmission. However, the roles and causation of these changes in bipolar disorder have been too complex to exactly determine the pathology of the disease. Furthermore, although some patients show remarkable improvement with lithium treatment for yet unknown reasons, others are refractory to lithium treatment. Therefore, developing an accurate and powerful biological model for bipolar disorder has been a challenge. The introduction of induced pluripotent stem-cell (iPSC) technology has provided a new approach. Here we have developed an iPSC model for human bipolar disorder and investigated the cellular phenotypes of hippocampal dentate gyrus-like neurons derived from iPSCs of patients with bipolar disorder. Guided by RNA sequencing expression profiling, we have detected mitochondrial abnormalities in young neurons from patients with bipolar disorder by using mitochondrial assays; in addition, using both patch-clamp recording and somatic Ca2+ imaging, we have observed hyperactive action-potential firing. This hyperexcitability phenotype of young neurons in bipolar disorder was selectively reversed by lithium treatment only in neurons derived from patients who also responded to lithium treatment. Therefore, hyperexcitability is one early endophenotype of bipolar disorder, and our model of iPSCs in this disease might be useful in developing new therapies and drugs aimed at its clinical treatment.Item Differential Resting-State Functional Connectivity of Striatal Subregions in Bipolar Depression and Hypomania(Mary Ann Liebert, 2016-04) Altinay, Murat I.; Hulvershorn, Leslie A.; Karne, Harish; Beall, Erik B.; Anand, Amit; Department of Psychiatry, School of MedicineBipolar disorder (BP) is characterized by periods of depression (BPD) and (hypo)mania (BPM), but the underlying state-related brain circuit abnormalities are not fully understood. Striatal functional activation and connectivity abnormalities have been noted in BP, but consistent findings have not been reported. To further elucidate striatal abnormalities in different BP states, this study investigated differences in resting-state functional connectivity of six striatal subregions in BPD, BPM, and healthy control (HC) subjects. Ninety medication-free subjects (30 BPD, 30 BPM, and 30 HC), closely matched for age and gender, were scanned using 3T functional magnetic resonance imaging (fMRI) acquired at resting state. Correlations of low-frequency blood oxygen level dependent signal fluctuations for six previously described striatal subregions were used to obtain connectivity maps of each subregion. Using a factorial design, main effects for differences between groups were obtained and post hoc pairwise group comparisons performed. BPD showed increased connectivity of the dorsal caudal putamen with somatosensory areas such as the insula and temporal gyrus. BPM group showed unique increased connectivity between left dorsal caudate and midbrain regions, as well as increased connectivity between ventral striatum inferior and thalamus. In addition, both BPD and BPM exhibited widespread functional connectivity abnormalities between striatal subregions and frontal cortices, limbic regions, and midbrain structures. In summary, BPD exhibited connectivity abnormalities of associative and somatosensory subregions of the putamen, while BPM exhibited connectivity abnormalities of associative and limbic caudate. Most other striatal subregion connectivity abnormalities were common to both groups and may be trait related.Item Disturbances of visual motion perception in bipolar disorder(Wiley Blackwell (Blackwell Publishing), 2014-06) O'Bryan, Rebecca A.; Brenner, Colleen A.; Hetrick, William P.; O'Donnell, Brian F.; Department of Psychiatry, IU School of MedicineOBJECTIVES: While cognitive deficits have been well documented in patients with bipolar disorder, visual perception has been less well characterized. Such deficits appear in schizophrenia, which shares genetic risk factors with bipolar disorder, and may contribute to disturbances in visual cognition and learning. METHODS: The present study investigated visual perception in bipolar disorder using psychophysical tests of contrast sensitivity, dot motion discrimination, and form discrimination. The relationship of these measures to mood state, medication status, and cognitive function was investigated. Sixty-one patients with type I bipolar disorder and 67 comparison subjects were tested. RESULTS: Results indicated a deficit in dot motion trajectory discrimination in both euthymic and ill individuals with bipolar disorder, as well as a global deficit in moving grating contrast sensitivity. Ill individuals with bipolar disorder were impaired in psychomotor processing, but this finding was not related to visual processing performance. CONCLUSIONS: These findings could be due to disturbances in specific visual pathways involved in the processing of motion properties, or to a more general deficit which impairs processing of temporally modulated stimuli.Item Genome-wide parametric linkage analyses of 644 bipolar pedigrees suggest susceptibility loci at chromosomes 16 and 20(Ovid Technologies (Wolters Kluwer) - Lippincott Williams & Wilkins, 2008-08) Ross, Jessica; Berrettini, Wade; Coryell, William; Gershon, Elliot S.; Badner, Judith A.; Kelsoe, John R.; McInnis, Melvin G.; McMahon, Francis J.; Murphy, Dennis L.; Nurnberger, John I.; Foroud, Tatiana; Rice, John P.; Scheftner, William B.; Zandi, Peter; Edenberg, Howard; Byerley, William; Department of Psychiatry, IU School of MedicineOBJECTIVE: Our aim is to map chromosomal regions that harbor loci that increase susceptibility to bipolar disorder. METHODS: We analyzed 644 bipolar families ascertained by the National Institute of Mental Health Human Genetics Initiative for bipolar disorder. The families have been genotyped with microsatellite loci spaced every approximately 10 cM or less across the genome. Earlier analyses of these pedigrees have been limited to nonparametric (model-free) methods and thus, information from unaffected subjects with genotypes was not considered. In this study, we used parametric analyses assuming dominant and recessive transmission and specifying a maximum penetrance of 70%, so that information from unaffecteds could be weighed in the linkage analyses. As in previous linkage analyses of these pedigrees, we analyzed three diagnostic categories: model 1 included only bipolar I and schizoaffective, bipolar cases (1565 patients of whom approximately 4% were schizoaffective, bipolar); model 2 included all individuals in model 1 plus bipolar II patients (1764 total individuals); and model 3 included all individuals in model 2 with the addition of patients with recurrent major depressive disorder (2046 total persons). RESULTS: Assuming dominant inheritance the highest genome-wide pair-wise logarithm of the odds (LOD) score was 3.2 with D16S749 using model 2 patients. Multipoint analyses of this region yielded a maximum LOD score of 4.91. Under recessive transmission a number of chromosome 20 markers were positive and multipoint analyses of the area gave a maximum LOD of 3.0 with model 2 cases. CONCLUSION: The chromosome 16p and 20 regions have been implicated by some studies and the data reported herein provide additional suggestive evidence of bipolar susceptibility genes in these regions.Item Grandma Grady's Grade-A Gray Day(IU Conscience Project, 2007) Galvin, Matthew R.Item New analyses provide supportive evidence for specific genes related to bipolar disorder(Wiley, 2021-05) Nurnberger, John I.; Psychiatry, School of MedicineItem Polygenic dissection of diagnosis and clinical dimensions of bipolar disorder and schizophrenia(Nature Publishing Group, 2014-09) Ruderfer, Douglas M.; Fanous, Ayman H.; Ripke, Stephan; McQuillin, Andrew; Amdur, Richard L.; Gejman, Pablo V.; O’Donovan, Michael C.; Andreassen, Ole A.; Djurovic, Srdjan; Hultman, Christina M.; Kelsoe, John R.; Jamain, Stephane; Landén, Mikael; Leboyer, Marion; Nimgaonkar, Vishwajit; Nurnberger, John; Smoller, Jordan W.; Craddock, Nick; Corvin, Aiden; Sullivan, Patrick F.; Holmans, Peter; Sklar, Pamela; Kendler, Kenneth S.; Department of Medical & Molecular Genetics, IU School of MedicineBipolar disorder and schizophrenia are two often severe disorders with high heritabilities. Recent studies have demonstrated a large overlap of genetic risk loci between these disorders but diagnostic and molecular distinctions still remain. Here, we perform a combined GWAS of 19,779 BP and SCZ cases versus 19,423 controls, in addition to a direct comparison GWAS of 7,129 SCZ cases versus 9,252 BP cases. In our case-control analysis, we identify five previously identified regions reaching genome-wide significance (CACNA1C, IFI44L, MHC, TRANK1, MAD1L1) and a novel locus near PIK3C2A. We create a polygenic risk score that is significantly different between BP and SCZ and show a significant correlation between a BP polygenic risk score and the clinical dimension of mania in SCZ patients. Our results indicate that first, combining diseases with similar genetic risk profiles improves power to detect shared risk loci and second, that future direct comparisons of BP and SCZ are likely to identify loci with significant differential effects. Identifying these loci should aid in the fundamental understanding of how these diseases differ biologically. These findings also indicate that combining clinical symptom dimensions and polygenic signatures could provide additional information that may someday be used clinically.Item Psychiatric blood biomarkers: avoiding jumping to premature negative or positive conclusions(Nature Publishing Group, 2015-03) Niculescu, A B; Levey, D; Le-Niculescu, H; Niculescu, E; Kurian, S M; Salomon, D; Department of Psychiatry, IU School of MedicineBlood biomarkers may provide a scientifically useful and clinically usable peripheral signal in psychiatry, as they have been doing for other fields of medicine. Jumping to premature conclusions, negative or positive, can create confusion in this field. Reproducibility is a hallmark of good science. We discuss some recent examples from this dynamic field, and show some new data in support of previously published biomarkers for suicidality (SAT1, MARCKS and SKA2). Methodological clarity and rigor in terms of biomarker discovery, validation and testing is needed. We propose a set of principles for what constitutes a good biomarker, similar in spirit to the Koch postulates used at the birth of the field of infectious diseases.