Pimavanserin Treatment for Psychosis in Patients with Dementia with Lewy Bodies: A Case Series.

BACKGROUND Many patients with dementia with Lewy bodies (DLB) experience cholinesterase inhibitor- and antipsychotic-resistant psychosis. The new second-generation antipsychotic pimavanserin has been used with some success in the treatment of psychosis in other forms of dementia, including Alzheimer disease and Parkinson disease dementia. It is possible that pimavanserin may also be useful in the treatment of psychosis in DLB. We sought to describe the disease course and treatment of psychosis in 4 patients with DLB who were prescribed pimavanserin after other medications failed to reduce the frequency or severity of hallucinations and delusions. CASE REPORT This is a case series of 4 male patients (ages 56 to 74 at the beginning of the reports) who developed DLB and psychosis (eg, visual illusions, visual and olfactory hallucinations, and paranoid delusions). All 4 patients were prescribed cholinesterase inhibitors (eg, donepezil or rivastigmine) prior to pimavanserin, and only 1 patient experienced improved psychosis while on cholinesterase inhibitors. All 3 patients who were prescribed first-generation antipsychotics (eg, haloperidol) or traditional second-generation antipsychotics (eg, olanzapine, risperidone, or quetiapine) experienced initial or lasting side effects with no improvement of psychosis. Conversely, all 4 patients tolerated pimavanserin well, and 3 of the 4 patients experienced significant improvement of psychosis (eg, fewer hallucinations, fewer delusions, reduced paranoia, and/or reduced distress or agitation related to hallucinations and delusions) when prescribed pimavanserin. CONCLUSIONS This case series suggests that pimavanserin is tolerable in older males with DLB and that it may be useful for the reduction of distressful hallucinations, delusions, and paranoia in patients with DLB.

Identifying probable dementia in undiagnosed Black and White Americans using machine learning in Veterans Health Administration electronic health records.

The application of machine learning (ML) tools in electronic health records (EHRs) can help reduce the underdiagnosis of dementia, but models that are not designed to reflect minority population may perpetuate that underdiagnosis. To address the underdiagnosis of dementia in both Black Americans (BAs) and white Americans (WAs), we sought to develop and validate ML models that assign race-specific risk scores. These scores were used to identify undiagnosed dementia in BA and WA Veterans in EHRs. More specifically, risk scores were generated separately for BAs (n=10K) and WAs (n=10K) in training samples of cases and controls by performing ML, equivalence mapping, topic modeling, and a support vector-machine (SVM) in structured and unstructured EHR data. Scores were validated via blinded manual chart reviews (n=1.2K) of controls from a separate sample (n=20K). AUCs and negative and positive predictive values (NPVs and PPVs) were calculated to evaluate the models. There was a strong positive relationship between SVM-generated risk scores and undiagnosed dementia. BAs were more likely than WAs to have undiagnosed dementia per chart review, both overall (15.3% vs 9.5%) and among Veterans with >90th percentile cutoff scores (25.6% vs 15.3%). With chart reviews as the reference standard and varied cutoff scores, the BA model performed slightly better than the WA model (AUC=0.86 with NPV=0.98 and PPV=0.26 at >90th percentile cutoff vs AUC=0.77 with NPV=0.98 and PPV=0.15 at >90th). The AUCs, NPVs, and PPVs suggest that race-specific ML models can assist in the identification of undiagnosed dementia, particularly in BAs. Future studies should investigate implementing EHR-based risk scores in clinics that serve both BA and WA Veterans.

Correlates of Conversion from Mild Cognitive Impairment to Dementia with Lewy Bodies: Data from the National Alzheimer's Coordinating Center.

BACKGROUND: Many patients with dementia with Lewy bodies (DLB) miss out on the best standards of care and psychosocial support due to diagnostic delays or inaccuracies following symptom onset. OBJECTIVE: This study seeks to identify baseline characteristics in individuals with mild cognitive impairment (MCI) that correlate with eventual conversion to DLB or Alzheimer's disease (AD). METHODS: Baseline neuropsychological and neuropsychiatric data were analyzed in National Alzheimer's Coordinating Center participants who completed the Uniform Data Set between 2006 and 2020 and subsequently converted from MCI to DLB or AD (n = 1632). RESULTS: Only 6% of participants with MCI converted to DLB. Among those who converted to DLB, multidomain amnestic MCI (aMCI) was the most common subtype at study entry. As part of logistic regression analyses, odds ratios (ORs) were estimated for conversion to DLB versus AD based on study-entry characteristics, adjusting for age, sex, education, and years to diagnosis. The strongest predictors of conversion to DLB (p≤0.0001) were nonamnestic MCI versus aMCI (OR 8.2, CI [5.0, 14]), multidomain MCI versus single-domain MCI (OR 2.7, CI [1.7. 4.2]), male sex (OR 4.2, CI [2.5, 7.1]), and presence of nighttime behaviors (OR 4.4 CI [2.8, 6.9]). CONCLUSION: A diagnosis of prodromal DLB should be considered in individuals with MCI who present with prominent executive/visuospatial deficits, neuropsychiatric symptoms, and less memory impairment. Early diagnosis of DLB may guide treatment planning, including the avoidance of antipsychotic medications in patients who develop psychotic symptoms, caregiver support, and initiation of early treatment(s) once medications become available.

Redefining transcriptional regulation of the APOE gene and its association with Alzheimer's disease.

The apolipoprotein E gene (APOE) is the strongest genetic risk factor for late-onset Alzheimer's disease (AD), yet the expression of APOE is not clearly understood. For example, it is unclear whether AD patients have elevated or decreased APOE expression or why the correlation levels of APOE RNA and the ApoE protein differ across studies. Likewise, APOE has a single CpG island (CGI) that overlaps with its 3'-exon, and this CGI's effect is unknown. We previously reported that the APOE CGI is highly methylated in human postmortem brain (PMB) and that this methylation is altered in AD frontal lobe. In this study, we comprehensively characterized APOE RNA transcripts and correlated levels of RNA expression with DNA methylation levels across the APOE CGI. We discovered the presence of APOE circular RNA (circRNA) and found that circRNA and full-length mRNA each constitute approximately one third of the total APOE RNA, with truncated mRNAs likely constituting some of the missing fraction. All APOE RNA species demonstrated significantly higher expression in AD frontal lobe than in control frontal lobe. Furthermore, we observed a negative correlation between the levels of total APOE RNA and DNA methylation at the APOE CGI in the frontal lobe. When stratified by disease status, this correlation was strengthened in controls but not in AD. Our findings suggest a possible modified mechanism of gene action for APOE in AD that involves not only the protein isoforms but also an epigenetically regulated transcriptional program driven by DNA methylation in the APOE CGI.

Detection of probable dementia cases in undiagnosed patients using structured and unstructured electronic health records.

BACKGROUND: Dementia is underdiagnosed in both the general population and among Veterans. This underdiagnosis decreases quality of life, reduces opportunities for interventions, and increases health-care costs. New approaches are therefore necessary to facilitate the timely detection of dementia. This study seeks to identify cases of undiagnosed dementia by developing and validating a weakly supervised machine-learning approach that incorporates the analysis of both structured and unstructured electronic health record (EHR) data. METHODS: A topic modeling approach that included latent Dirichlet allocation, stable topic extraction, and random sampling was applied to VHA EHRs. Topic features from unstructured data and features from structured data were compared between Veterans with (n = 1861) and without (n = 9305) ICD-9 dementia codes. A logistic regression model was used to develop dementia prediction scores, and manual reviews were conducted to validate the machine-learning results. RESULTS: A total of 853 features were identified (290 topics, 174 non-dementia ICD codes, 159 CPT codes, 59 medications, and 171 note types) for the development of logistic regression prediction scores. These scores were validated in a subset of Veterans without ICD-9 dementia codes (n = 120) by experts in dementia who performed manual record reviews and achieved a high level of inter-rater agreement. The manual reviews were used to develop a receiver of characteristic (ROC) curve with different thresholds for case detection, including a threshold of 0.061, which produced an optimal sensitivity (0.825) and specificity (0.832). CONCLUSIONS: Dementia is underdiagnosed, and thus, ICD codes alone cannot serve as a gold standard for diagnosis. However, this study suggests that imperfect data (e.g., ICD codes in combination with other EHR features) can serve as a silver standard to develop a risk model, apply that model to patients without dementia codes, and then select a case-detection threshold. The study is one of the first to utilize both structured and unstructured EHRs to develop risk scores for the diagnosis of dementia.

Endophenotypes in Schizophrenia: Digging Deeper to Identify Genetic Mechanisms.

Schizophrenia (SZ) is a severe psychotic disorder that is highly heritable and common in the general population. The genetic heterogeneity of SZ is substantial, with contributions from common, rare, and de novo variants, in addition to environmental factors. Large genome-wide association studies have detected many variants that are associated with SZ, yet the pathways by which these variants influence risk remain largely unknown. SZ is also clinically heterogeneous, with patients exhibiting a broad range of deficits and symptom severity that vary over the course of illness and treatment, which has complicated efforts to identify risk variants. However, the underlying brain dysfunction forms a more stable trait marker that quantitative neurocognitive and neurophysiological endophenotypes may be able to objectively measure. These endophenotypes are less likely to be heterogeneous than the disorder and provide a neurobiological context to detect risk variants and underlying pathways among genes associated with SZ diagnosis. Furthermore, many endophenotypes are translational into animal model systems, allowing for direct evaluation of the neural circuit dysfunctions and neurobiological substrates. We review a selection of the most promising SZ endophenotypes, including prepulse inhibition, mismatch negativity, oculomotor antisaccade, letter-number sequencing, and continuous performance tests. We also highlight recent findings from large consortia that suggest the potential role of genes, particularly in the neuregulin and glutamate pathways, in several of these endophenotypes. Although endophenotypes require additional time and effort to assess, the insight into the underlying neurobiology that they provide may ultimately reveal the underlying genetic architecture for SZ and suggest novel treatment targets.

APOE DNA methylation is altered in Lewy body dementia.

INTRODUCTION: Inheritance of the ε4 allele of apolipoprotein E (APOE) increases a person's risk of developing both Alzheimer's disease (AD) and Lewy body dementia (LBD), yet the underlying mechanisms behind this risk are incompletely understood. The recent identification of reduced APOE DNA methylation in AD postmortem brains prompted this study to investigate APOE methylation in LBD. METHODS: Genomic DNA from postmortem brain tissues (frontal lobe and cerebellum) of neuropathological pure (np) controls and npAD, LBD + AD, and npLBD subjects were bisulfite pyrosequenced. DNA methylation levels of two APOE subregions were then compared for these groups. RESULTS: APOE DNA methylation was significantly reduced in npLBD compared with np controls, and methylation levels were lowest in the LBD + AD group. DISCUSSION: Given that npLBD and npAD postmortem brains shared a similar reduction in APOE methylation, it is possible that an aberrant epigenetic change in APOE is linked to risk for both diseases.

A Genetic Study of Psychosis in Huntington's Disease: Evidence for the Involvement of Glutamate Signaling Pathways.

BACKGROUND: Psychotic symptoms of delusions and hallucinations occur in about 5% of persons with Huntington's disease (HD). The mechanisms underlying these occurrences are unknown, but the same symptoms also occur in schizophrenia, and thus genetic risk factors for schizophrenia may be relevant to the development of psychosis in HD. OBJECTIVE: To investigate the possible role of genes associated with schizophrenia in the occurrence of psychotic symptoms in HD. METHODS: DNA from subjects with HD and psychosis (HD+P; n = 47), subjects with HD and no psychosis (HD-P; n = 126), and controls (CTLs; n = 207) was genotyped using the Infinium PsychArray-24 v1.1 BeadChip. The allele frequencies of single-nucleotide polymorphisms (SNPs) that were previously associated with schizophrenia and related psychiatric disorders were compared between these groups. RESULTS: Of the 30 candidate genes tested, 10 showed an association with psychosis in HD. The majority of these genes, including CTNNA2, DRD2, ERBB4, GRID2, GRIK4, GRM1, NRG1, PCNT, RELN, and SLC1A2, demonstrate network interactions related to glutamate signaling. CONCLUSIONS: This study suggests genetic associations between several previously identified candidate genes for schizophrenia and the occurrence of psychotic symptoms in HD. These data support the potential role of genes related to glutamate signaling in HD psychosis.

Biofluid biomarkers of traumatic brain injury.

PRIMARY OBJECTIVE: The purpose of this paper is to review the clinical and research utility and applications of blood, cerebrospinal fluid (CSF), and cerebral microdialysis biomarkers in traumatic brain injury (TBI). RESEARCH DESIGN: Not applicable. METHODS AND PROCEDURES: A selective review was performed on these biofluid biomarkers in TBI. MAIN OUTCOME AND RESULTS: Neurofilament heavy chain protein (NF-H), glial fibrillary acidic protein (GFAP), ubiquitin C-terminal hydrolase-L1 (UCHL1), neuron-specific enolase (NSE), myelin basic protein (MBP), tau, and s100ß blood biomarkers are elevated during the acute phase of severe head trauma but have key limitations in their research and clinical applications to mild TBI (mTBI). CSF biomarkers currently provide the best reflection of the central nervous system (CNS) pathobiological processes in TBI. Both animal and human studies of TBI have demonstrated the importance of serial sampling of biofluids and suggest that CSF biomarkers may be better equipped to characterize both TBI severity and temporal profiles. CONCLUSIONS: The identification of biofluid biomarkers could play a vital role in identifying, diagnosing, and treating the underlying individual pathobiological changes of TBI. CNS-derived exosomes analyzed by ultra-high sensitivity detection methods have the potential to identify blood biomarkers for the range of TBI severity and time course.

Cerebrospinal fluid biomarkers for Alzheimer's and vascular disease vary by age, gender, and APOE genotype in cognitively normal adults.

BACKGROUND: This study sought to evaluate gender and APOE genotype-related differences in the concentrations of cerebrospinal fluid (CSF) biomarkers for Alzheimer's disease (AD) and cerebrovascular injury across the life span of cognitively normal adults. METHODS: CSF amyloid beta1-42 (Aß42), phospho-tau-181 (p-tau181), and total tau were measured in 331 participants who were between the ages of 21 and 100. CSF E-selectin and vascular cell adhesion protein 1 (VCAM1) were measured in 249 participants who were between the ages of 50 and 100. RESULTS: CSF total tau and p-tau181 increased with age over the adult life span (p < 0.01) with no gender differences in those increases. CSF Aß42 concentration varied according to age, gender, and APOE genotype (interaction of age × gender × Îµ4, p = 0.047). CSF VCAM1, but not E-selectin, increased with age (p < 0.01), but both were elevated in men compared to women (p < 0.01). CONCLUSIONS: Female APOE-ε4 carriers appear at higher risk for AD after age 50. In contrast, men may experience a relatively higher rate of cerebrovascular injury in middle and early old age.