Seonjoo Lee

Differential involvement of striato- and cerebello-thalamo-cortical pathways in tremor- and akinetic/rigid-predominant Parkinson's disease

Parkinsons disease (PD) presents clinically with varying degrees of resting tremor, rigidity, and bradykinesia. For decades, striatal-thalamo-cortical (STC) dysfunction has been implied in bradykinesia and rigidity, but does not explain resting tremor in PD. To understand the roles of cerebello-thalamo-cortical (CTC) and STC circuits in the pathophysiology of the heterogeneous clinical presentation of PD, we collected functional magnetic resonance imaging (fMRI) data from 17 right-handed PD patients [nine tremor predominant (PDT) and eight akinetic-rigidity predominant (PDAR)] and 14 right-handed controls while they performed internally-guided (IG) sequential finger tapping tasks. The percentage of voxels activated in regions constituting the STC and CTC [divided as cerebellar hemisphere-thalamo-cortical (CHTC) and vermis-thalamo-cortical (CVTC)] circuits was calculated. Multivariate analysis of variance compared the activation patterns of these circuits between study groups. Compared to controls, both PDAR and PDT subjects displayed an overall increase in the percentage of voxels activated in both STC and CTC circuits. These increases reached statistical significance in contralateral STC and CTC circuits for PDT subjects, and in contralateral CTC pathways for PDAR subjects. Comparison of PDAR and PDT subjects revealed significant differences in ipsilateral STC (P=0.005) and CTC (P=0.043 for CHTC and P=0.003 for CVTC) circuits. These data support the differential involvement of STC and CTC circuits in PD subtypes, and help explain the heterogeneous presentation of PD symptoms. These findings underscore the importance of integrating CTC circuits in understanding PD and other disorders of the basal ganglia.

Olfactory deficits predict cognitive decline and Alzheimer dementia in an urban community

Objective: To determine the predictive utility of baseline odor identification deficits for future cognitive decline and the diagnosis of Alzheimer disease (AD) dementia. Methods: In a multiethnic community cohort in North Manhattan, NY, 1,037 participants without dementia were evaluated with the 40-item University of Pennsylvania Smell Identification Test (UPSIT). In 757 participants, follow-up occurred at 2 years and 4 years. Results: In logistic regression analyses, lower baseline UPSIT scores were associated with cognitive decline (relative risk 1.067 per point interval; 95% confidence interval [CI] 1.040, 1.095; p < 0.0001), and remained significant (relative risk 1.065 per point interval; 95% CI 1.034, 1.095; p < 0.0001) after including covariates. UPSIT, but not Selective Reminding Test–total immediate recall, predicted cognitive decline in participants without baseline cognitive impairment. During follow-up, 101 participants transitioned to AD dementia. In discrete time survival analyses, lower baseline UPSIT scores were associated with transition to AD dementia (hazard ratio 1.099 per point interval; 95% CI 1.067, 1.131; p < 0.0001), and remained highly significant (hazard ratio 1.072 per point interval; 95% CI 1.036, 1.109; p < 0.0001) after including demographic, cognitive, and functional covariates. Conclusions: Impairment in odor identification was superior to deficits in verbal episodic memory in predicting cognitive decline in cognitively intact participants. The findings support the cross-cultural use of a relatively inexpensive odor identification test as an early biomarker of cognitive decline and AD dementia. Such testing may have the potential to select/stratify patients in treatment trials of cognitively impaired patients or prevention trials in cognitively intact individuals.

Olfactory identification deficits and increased mortality in the community.

To examine the association between odor identification deficits and future mortality in a multiethnic community cohort of older adults.

Independent Component Analysis Involving Autocorrelated Sources With an Application to Functional Magnetic Resonance Imaging

Independent component analysis (ICA) is an effective data-driven method for blind source separation. It has been successfully applied to separate source signals of interest from their mixtures. Most existing ICA procedures are carried out by relying solely on the estimation of the marginal density functions, either parametrically or nonparametrically. In many applications, correlation structures within each source also play an important role besides the marginal distributions. One important example is functional magnetic resonance imaging (fMRI) analysis where the brain-function-related signals are temporally correlated. In this article, we consider a novel approach to ICA that fully exploits the correlation structures within the source signals. Specifically, we propose to estimate the spectral density functions of the source signals instead of their marginal density functions. This is made possible by virtue of the intrinsic relationship between the (unobserved) sources and the (observed) mixed signals. Our methodology is described and implemented using spectral density functions from frequently used time series models such as autoregressive moving average (ARMA) processes. The time series parameters and the mixing matrix are estimated via maximizing the Whittle likelihood function. We illustrate the performance of the proposed method through extensive simulation studies and a real fMRI application. The numerical results indicate that our approach outperforms several popular methods including the most widely used fastICA algorithm. This article has supplementary material online.

Relation of platelet count to bleeding and vascular complications in patients undergoing coronary angiography.

Vascular and bleeding complications are associated with significant morbidity and mortality, limited data are available on the relation between these complications and the platelet count in patients undergoing coronary angiography. We, therefore, performed a retrospective cohort analysis of 3,466 consecutive adults undergoing coronary angiography at a single institution during a 2-year period. The mean + or - SD age was 60 + or - 13 years; 58% of the patients were men, 67% were white, and 27% were black. The mean platelet count was 242 + or - 86 x 10(9)/L. A total of 143 bleeding or vascular complications (4.2%), as defined using the American College of Cardiology CathPCI Registry criteria, a part of the American College of Cardiology National Cardiovascular Disease Registry, occurred. The risk of complications increased with increasing platelet counts. Compared to the quartile with the lowest platelet counts, the odds ratio (OR) for complications was 1.41 for the second quartile (95% confidence interval 0.83 to 2.37, p = 0.20), 1.74 for the third quartile (95% confidence interval 1.04 to 2.93, p = 0.04), and 2.04 for the fourth quartile (95% confidence interval 1.21 to 3.44, p = 0.008). On multivariate logistic regression analysis, age, percutaneous coronary intervention, and increasing platelet counts were independent predictors of bleeding and vascular complications. When the analysis was limited to the 2,220 patients undergoing diagnostic coronary angiography without percutaneous coronary intervention, an increasing platelet quartile was a significant predictor of vascular and/or bleeding complications (OR 1.88, p = 0.08; OR 2.48, p = 0.01; OR 2.52, p = 0.01 for the second, third, and fourth quartiles, respectively). In conclusion, the baseline platelet count was a strong and independent risk factor for bleeding and vascular complications in patients undergoing coronary angiography.

Omega-3 polyunsaturated fatty acid supplementation and white matter changes in major depression.

White matter abnormalities are implicated in major depressive disorder (MDD). As omega-3 polyunsaturated fatty acids (PUFAs) are low in MDD and affect myelination, we hypothesized that PUFA supplementation may alleviate depression through improving white matter integrity. Acutely depressed MDD patients (n = 16) and healthy volunteers (HV, n = 12) had 25-direction diffusion tensor imaging before and after 6 weeks of fish oil supplementation. Plasma phospholipid omega-3 PUFAs eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), and omega-6 PUFA arachidonic acid (AA) levels were determined before and after supplementation using high-throughput extraction and gas chromatography and expressed as a percentage of total phospholipids (PUFA%). Fractional anisotropy (FA) was computed using a least-squares-fit diffusion tensor with non-linear optimization. Regression analyses were performed with changes in PUFA levels or Hamilton Depression Rating Scale scores as predictors, voxel-wise difference maps of FA as outcome, covariates age and sex, with family-wise correction for multiple comparisons. Increases in plasma phospholipid DHA% (but not EPA% or AA%) after fish oil predicted increases in FA in MDD but not HV, in a cluster including genu and body of the corpus callosum, and anterior corona radiata and cingulum (cluster-level p < 0.001, peak t-score = 8.10, p = 0.002). There was a trend for greater change in FA in MDD responders over nonresponders (t = -1.874, df = 13.56, p = 0.08). Decreased depression severity predicted increased FA in left corticospinal tract and superior longitudinal fasciculus (cluster-level p < 0.001, peak t-score = 5.04, p = 0.0001). Increased FA correlated with increased DHA% and decreased depression severity after fish oil supplementation suggests therapeutic effects of omega-3 PUFAs may be related to improvements in white matter integrity.

Poisson factor models with applications to non-normalized microRNA profiling

MOTIVATION Next-generation (NextGen) sequencing is becoming increasingly popular as an alternative for transcriptional profiling, as is the case for micro RNAs (miRNA) profiling and classification. miRNAs are a new class of molecules that are regulated in response to differentiation, tumorigenesis or infection. Our primary motivating application is to identify different viral infections based on the induced change in the host miRNA profile. Statistical challenges are encountered because of special features of NextGen sequencing data: the data are read counts that are extremely skewed and non-negative; the total number of reads varies dramatically across samples that require appropriate normalization. Statistical tools developed for microarray expression data, such as principal component analysis, are sub-optimal for analyzing NextGen sequencing data. RESULTS We propose a family of Poisson factor models that explicitly takes into account the count nature of sequencing data and automatically incorporates sample normalization through the use of offsets. We develop an efficient algorithm for estimating the Poisson factor model, entitled Poisson Singular Value Decomposition with Offset (PSVDOS). The method is shown to outperform several other normalization and dimension reduction methods in a simulation study. Through analysis of an miRNA profiling experiment, we further illustrate that our model achieves insightful dimension reduction of the miRNA profiles of 18 samples: the extracted factors lead to more accurate and meaningful clustering of the cell lines. AVAILABILITY The PSVDOS software is available on request.

Associations Among Child Abuse, Depression, and Interleukin-6 in Pregnant Adolescents: Paradoxical Findings

Objective Limited data exist on child abuse–related immune variation during pregnancy, despite implications for maternal and infant health and extensive data showing that abuse history and depression are related to increased inflammation in other populations. This study examined associations among child abuse, depression, circulating levels of inflammatory markers, and perinatal health in pregnant adolescents, a group at high risk for childhood abuse and poor birth outcomes. Methods Pregnant teenagers (n = 133; 14–19 years; 89.5% Latina) reported on abuse and depression and had two blood draws (24–27 and 34–37 gestational weeks, second and third trimesters, respectively) for interleukin-6 (IL-6) and C-reactive protein; birth outcomes were collected. Results Abuse and depression interacted to predict higher IL-6 at second trimester (B = 0.006, p = .011) such that severely abused adolescents with high depression had higher IL-6 relative to severely abused adolescents with low depression; depression did not differentiate IL-6 levels for those with low abuse severity. Abuse and IL-6 also interacted to predict gestational age at birth (B = 0.004, p = .040) such that those with low abuse and high IL-6 and those with high abuse and low IL-6 had infants with earlier gestational age at birth. Cortisol at the second trimester mediated the association between IL-6 and gestational age at birth (indirect effect estimate=−0.143, p < .039). Conclusions Depression severity distinguished IL-6 levels among more severely abused pregnant Latina adolescents, but it was unrelated to IL-6 among less severely abused adolescents. Cortisol explained the relationship between IL-6 and earlier gestational age at birth. Multiple adversities and inflammation may influence birth outcomes and potentially affect intergenerational health.

Neuropsychiatric effects of neurodegeneration of the medial versus lateral ventral prefrontal cortex in humans

Animal evidence suggests that a brain network involving the medial and rostral ventral prefrontal cortex (PFC) is central for threat response and arousal and a network involving the lateral and caudal PFC plays an important role in reward learning and behavioral control. In this study, we contrasted the neuropsychiatric effects of degeneration of the medial versus lateral PFC in 43 patients with Frontotemporal dementia (FTD) and 11 patients with Corticobasal Syndrome (CBS) using MRI, the Neuropsychiatric Inventory (NPI), and the Sorting, Tower, Twenty Questions, and Fluency tests of the Delis-Kaplan Executive Function System (D-KEFS). Deviations in MRI grey matter volume from 86 age-matched healthy control subjects were determined for the patients using FreeSurfer. Multivariate regression was used to determine which brain areas were associated with specific neuropsychiatric and cognitive symptoms. Decreased grey matter volume of the right medial ventral PFC was associated with increased anxiety and apathy, decreased volume of the right lateral ventral PFC with apathy and inappropriate repetitive behaviors, and of the left lateral ventral PFC with poor performance on the sorting and Twenty Questions task in patients with FTD and CBS. Similar to in animal studies, damage to the medial OFC appears to be associated with a disruption of arousal, and damage to the lateral OFC appears to be associated with deficits in trial-and-error learning and behavioral dysregulation. Studies of brain dysfunction in humans are valuable to bridge animal and human neuropsychiatric research.

Increased functional connectivity between the default mode and salience networks in unmedicated adults with obsessive-compulsive disorder

Deficits in attention have been implicated in Obsessive‐Compulsive Disorder (OCD), yet their neurobiological bases are poorly understood. In unmedicated adults with OCD (n = 30) and healthy controls (n = 32), they used resting state functional connectivity MRI (rs‐fcMRI) to examine functional connectivity between two neural networks associated with attentional processes: the default mode network (DMN) and the salience network (SN). They then used path analyses to examine putative relationships across three variables of interest: DMN‐SN connectivity, attention, and OCD symptoms. In the OCD compared with healthy control participants, there was significantly reduced inverse connectivity between the anterior medial prefrontal cortex (amPFC) and the anterior insular cortex, regions within the DMN and SN, respectively. In OCD, reduced inverse DMN‐SN connectivity was associated with both increased OCD symptom severity and decreased sustained attention. Path analyses were consistent with a potential mechanistic explanation: OCD symptoms are associated with an imbalance in DMN‐SN networks that subserve attentional processes and this effect of OCD on DMN‐SN connectivity is associated with decreased sustained attention. This work builds upon a growing literature suggesting that reduced inverse DMN‐SN connectivity may represent a trans‐diagnostic marker of attentional processes and suggests a potential mechanistic account of the relationship between OCD and attention. Reduced inverse DMN‐SN connectivity may be an important target for treatment development to improve attention in individuals with OCD. Hum Brain Mapp 38:678–687, 2017.