Low CD49d expression in newly diagnosed chronic lymphocytic leukaemia may be associated with high-risk features and reduced treatment-free-intervals.

This study was carried out to assess the prognostic power of low CD49d expression (≥10%) in newly diagnosed CLL patients using a previously described cohort. Eighty-five patients were included. Median age at diagnosis; 70 years (43-88); CD49d was expressed in 33/85 (38.8%); 23/33 (69.7%) at ≥30% referred to as 'HiCD49d' and 10/33 (30.3%) between 10 and 30% with a bimodal pattern on scatterplot analysis referred to as 'LoCD49d'. Eleven patients (12.9%) presented as Binet stage B, of whom 8 (72.7%) were CD49d+ (HiCD49d 7/8; LoCD49d 1/8). Seven of 81 patients (8.6%) were NOTCH1 mutated and all were CD49d+ (p ≤ .01). IgVH analysis was performed on 29 (87.8%) of the CD49d+ cases, of whom 21 (72.4%) were unmutated and 8 (27.6%) were mutated. CD38+/CD49d+ accounted for 11/20 (55%) (CD38+/HiCD49D: 9/11; CD38+/LoCD49D: 2/11). At 42 months, treatment had been initiated in 18/85 (21%) patients, of these 10/33 (30.3%) were CD49d+ versus 8/52 (15.4%) of the CD49d- group. The median treatment free interval for the CD49d+ group was 11 months (HiCD49d; 14.5 months, LoCD49d; 11 months) compared to 21.5 months for the CD49d- group. These findings suggest that the predictive value of CD49d expression is retained at expression levels down to 10%.

Neurobiological underpinnings of suicidalbehavior: Integrating data from clinicaland biological studies

Background and Objectives: Every year, suicide accounts for approximatelyone million preventable deaths worldwide. Suicidal behavior is complex andmulti-determined with risk factors identified in multiple domains including clinical, genetic,environmental, behavioral, neurophysiological, and neurocognitive. Modelingcausal pathways that integrate these factors may assist in better identification of high-riskindividuals would allow for effective preventive intervention.Methods: Published literature in the English language was reviewed to identify evidencesupporting a multi-dimensional model of putative causal pathways for suicidal behavior.Results: There is evidence that clinical, neurochemical, neuroendocrine, neurocognitive,and neurophysiological contributory factors may be useful as intermediate phenotypes in describingputative causal pathways from genetics and early-life adversity to suicidal acts.Conclusions: Determining the causes of suicidal behavior involves integrating risk factorsfrom multiple domains (AU)