Clinical features and lymphocyte immunophenotyping analysis in primary immunodeficiency patients with non-transplant lymphoproliferative disorders.

Lymphoproliferative disorders (LPD) comprise a heterogeneous group and are originally classified into the "Disease of immune dysregulation" category. Of 96 Taiwanese patients during 2003-2022, 31 (median 66, range 0.03-675 months) developed LPD, mainly including palpable lymphadenopathy (in 10 patients), intestinal lymphadenopathy associated with refractory inflammatory bowel disease (IBD in 8) and hepatosplenomegaly (in 7) during long-term follow-up (median 144, range 3-252 months). They distributed in the categories of antibody deficiency (2 CVID, 2 TTC37, PIK3CD, PIK3R1 and AICDA each), phagocyte (4 CYBB, 1 STAT1 and 1 IFNRG1), immune dysregulation (2 FOXP3, 2 XIAP and 2 HLH), combined immunodeficiencies (2 IL2RG; CD40L, ZAP70 and unknown each), syndromic features (2 STAT3-LOF, 1 WAS and 1 ATM) and three with anti-IFN-γ autoantibodies. An increased senescent (CD8 + CD57+) and CD21-low, disturbed transitional B (CD38 + IgM++), plasmablast B (CD38++IgM-), memory B (CD19 + CD27+) and TEMRA (CD27-IgD-) components were often observed in cross-sectional immunophenotyping and trended to develop LPD.

Cerebrospinal fluid biomarker profiling of diverse pathophysiological domains in Alzheimer's disease.

INTRODUCTION: While Alzheimer's disease (AD) is defined by amyloid-ß plaques and tau tangles in the brain, it is evident that many other pathophysiological processes such as inflammation, neurovascular dysfunction, oxidative stress, and metabolic derangements also contribute to the disease process and that varying contributions of these pathways may reflect the heterogeneity of AD. Here, we used a previously validated panel of cerebrospinal fluid (CSF) biomarkers to explore the degree to which different pathophysiological domains are dysregulated in AD and how they relate to each other. METHODS: Twenty-five CSF biomarkers were analyzed in individuals with a clinical diagnosis of AD verified by positive CSF AD biomarkers (AD, n = 54) and cognitively unimpaired controls negative for CSF AD biomarkers (CU-N, n = 26) using commercial single- and multi-plex immunoassays. RESULTS: We noted that while AD was associated with increased levels of only three biomarkers (MMP-10, FABP3, and 8OHdG) on a group level, half of all AD participants had increased levels of biomarkers belonging to at least two pathophysiological domains reflecting the diversity in AD. LASSO modeling showed that a panel of FABP3, 24OHC, MMP-10, MMP-2, and 8OHdG constituted the most relevant and minimally correlated set of variables differentiating AD from CU-N. Interestingly, factor analysis showed that two markers of metabolism and oxidative stress (24OHC and 8OHdG) contributed independent information separate from MMP-10 and FABP3 suggestive of two independent pathophysiological pathways in AD, one reflecting neurodegeneration and vascular pathology, and the other associated with metabolism and oxidative stress. DISCUSSION: Better understanding of the heterogeneity among individuals with AD and the different contributions of pathophysiological processes besides amyloid-ß and tau will be crucial for optimizing personalized treatment strategies. Highlights: A panel of 25 highly validated biomarker assays were measured in CSF.MMP10, FABP3, and 8OHdG were increased in AD in univariate analysis.Many individuals with AD had increased levels of more than one biomarker.Markers of metabolism and oxidative stress contributed to an AD multianalyte profile.Assessing multiple biomarker domains is important to understand disease heterogeneity.

Examining the Relationships Between Indoor Environmental Quality Parameters Pertaining to Light, Noise, Temperature, and Humidity and the Behavioral and Psychological Symptoms of People Living With Dementia: Scoping Review.

BACKGROUND: A common challenge for individuals caring for people with Alzheimer disease and related dementias is managing the behavioral and psychological symptoms of dementia (BPSD). Effective management of BPSD will increase the quality of life of people living with dementia, lessen caregivers' burden, and lower health care cost. OBJECTIVE: In this review, we seek to (1) examine how indoor environmental quality parameters pertaining to light, noise, temperature, and humidity are associated with BPSD and how controlling these parameters can help manage these symptoms and (2) identify the current state of knowledge in this area, current gaps in the research, and potential future directions. METHODS: Searches were conducted in the CINAHL, Embase, MEDLINE, and PsycINFO databases for papers published from January 2007 to February 2024. We searched for studies examining the relationship between indoor environmental quality parameters pertaining to light, noise, temperature, and humidity and BPSD. RESULTS: A total of 3123 papers were identified in the original search in October 2020. After an additional 2 searches and screening, 38 (0.69%) of the 5476 papers were included. Among the included papers, light was the most studied environmental factor (34/38, 89%), while there were fewer studies (from 5/38, 13% to 11/38, 29%) examining the relationships between other environmental factors and BPSD. Of the 38 studies, 8 (21%) examined multiple indoor environmental quality parameters. Subjective data were the only source of environmental assessments in 6 (16%) of the 38 studies. The findings regarding the relationship between agitation and light therapy are conflicted, while the studies that examined the relationship between BPSD and temperature or humidity are all observational. The results suggest that when the environmental factors are deemed overstimulating or understimulating for an individual with dementia, the behavioral symptoms tend to be exacerbated. CONCLUSIONS: The findings of this scoping review may inform the design of long-term care units and older adult housing to support aging in place. More research is still needed to better understand the relationship between indoor environmental quality parameters and BPSD, and there is a need for more objective measurements of both the indoor environmental quality parameters and behavioral symptoms. One future direction is to incorporate objective sensing and advanced computational methods in real-time assessments to initiate just-in-time environmental interventions. Better management of BPSD will benefit patients, caregivers, and the health care system.

Identification of Novel Biomarkers for Alzheimer's Disease and Related Dementias Using Unbiased Plasma Proteomics.

Alzheimer's disease (AD) and related dementias (ADRD) is a complex disease with multiple pathophysiological drivers that determine clinical symptomology and disease progression. These diseases develop insidiously over time, through many pathways and disease mechanisms and continue to have a huge societal impact for affected individuals and their families. While emerging blood-based biomarkers, such as plasma p-tau181 and p-tau217, accurately detect Alzheimer neuropthology and are associated with faster cognitive decline, the full extension of plasma proteomic changes in ADRD remains unknown. Earlier detection and better classification of the different subtypes may provide opportunities for earlier, more targeted interventions, and perhaps a higher likelihood of successful therapeutic development. In this study, we aim to leverage unbiased mass spectrometry proteomics to identify novel, blood-based biomarkers associated with cognitive decline. 1,786 plasma samples from 1,005 patients were collected over 12 years from partcipants in the Massachusetts Alzheimer's Disease Research Center Longitudinal Cohort Study. Patient metadata includes demographics, final diagnoses, and clinical dementia rating (CDR) scores taken concurrently. The Proteograph™ Product Suite (Seer, Inc.) and liquid-chromatography mass-spectrometry (LC-MS) analysis were used to process the plasma samples in this cohort and generate unbiased proteomics data. Data-independent acquisition (DIA) mass spectrometry results yielded 36,259 peptides and 4,007 protein groups. Linear mixed effects models revealed 138 differentially abundant proteins between AD and healthy controls. Machine learning classification models for AD diagnosis identified potential candidate biomarkers including MBP, BGLAP, and APoD. Cox regression models were created to determine the association of proteins with disease progression and suggest CLNS1A, CRISPLD2, and GOLPH3 as targets of further investigation as potential biomarkers. The Proteograph workflow provided deep, unbiased coverage of the plasma proteome at a speed that enabled a cohort study of almost 1,800 samples, which is the largest, deep, unbiased proteomics study of ADRD conducted to date.