Malformations of the hippocampal formation and amygdala have been implicated in several neurodevelopmental disorders; yet relatively little is known about their normal structural development. The purpose of this study was to characterize the early developmental trajectories of the hippocampus and amygdala in the rhesus macaques (Macaca mulatta) using noninvasive MRI techniques. T1-weighted structural scans of 22 infant and juvenile monkeys (11 male, 11 female) were obtained between 1 week and approximately 2 yrs of age. Ten animals (five males, five females) were scanned multiple times and 12 monkeys (six males, six females) were scanned once between 1 and 4 weeks of age. Both structures exhibited significant age-related changes throughout the first 2 yrs of life that were not explained by overall brain development. The hippocampal formation increased 117.05% in males and 110.86% in females. No sex differences were evident, but the left hemisphere was significantly larger than the right. The amygdala increased 86.49% in males and 72.94% in females with males exhibiting a larger right than left amygdala. For both structures, the most substantial volumetric increases were seen within the first month, but the hippocampal formation appeared to develop more slowly than the amygdala with the rate of hippocampal maturation stabilizing around 11 months and that of amygdala maturation stabilizing around 8 months. Differences in volumetric developmental trajectories of the hippocampal formation and amygdala largely mirror differences in the timing of the functional development of these structures. The current results emphasize the importance of including early postnatal ages when assessing developmental trajectories of neuroanatomical structures and reinforces the utility of nonhuman primates in the assessment of normal developmental patterns.

The prevalence of Toxoplasma gondii (TOXO) infection in schizophrenia (SCZ) is elevated compared to controls (odds ratio = 2.73). TOXO infection is associated with psychomotor slowing in rodents and non-psychiatric humans. Latency of the acoustic startle response, an index of neural processing speed, is the time it takes for a startling stimulus to elicit the reflexive response through a three-synapse subcortical circuit. We report a significant slowing of latency in TOXO seropositive SCZ vs. seronegative SCZ, and in TOXO seropositive controls vs. seronegative controls. Latency was likewise slower in SCZ subjects than in controls. These findings indicate a slowing of neural processing speed with chronic TOXO infection; the slowest startle latency was seen in the TOXO seropositive SCZ group.

Background/Aims To examine the relationship of biological mediators (cytokines, stress hormones), psychosocial, obstetric history, and demographic factors in the early prediction of preterm birth (PTB) using a comprehensive logistic regression model incorporating diverse risk factors. Methods In this prospective case-control study, maternal serum biomarkers were quantified at 9–23 weeks’ gestation in 60 women delivering at <37 weeks compared to 123 women delivering at term. Biomarker data were combined with maternal sociodemographic factors and stress data into regression models encompassing 22 preterm risk factors and 1st-order interactions. Results Among individual biomarkers, we found that macrophage migration inhibitory factor (MIF), interleukin-10, C-reactive protein (CRP), and tumor necrosis factor-α were statistically significant predictors of PTB at all cutoff levels tested (75th, 85th, and 90th percentiles). We fit multifactor models for PTB prediction at each biomarker cutoff. Our best models revealed that MIF, CRP, risk-taking behavior, and low educational attainment were consistent predictors of PTB at all biomarker cutoffs. The 75th percentile cutoff yielded the best predicting model with an area under the ROC curve of 0.808 (95% CI 0.743–0.874). Conclusion Our comprehensive models highlight the prominence of behavioral risk factors for PTB and point to MIF as a possible psychobiological mediator.

Background: Little is known about progression of and risk factors for sleep disordered breathing (SDB) in old age. We prospectively examined elderly volunteers to understand how changes in body weight are related to SDB for a period of 20–30 years. Methods: Participants were 30 surviving members of a community-based cohort (mean entry age = 57.8) studied over a median follow-up of 23.4 years. SDB was quantified as the apnea–hypopnea index (AHI) via in-lab polysomnography from 215 nights, representing 733.3 person-years of follow-up. Weights were recorded in kilograms. We used linear regression to derive individual trajectories of AHI and weight regressed on time. Results: Individuals had relatively low AHI (X = 2.3 [SD = 3.5]) and body mass index (kg/m2; X = 24.6 [SD = 4.6]) at entry. Rates of change in AHI were characterized by positive slopes and linear increases by least squares regression. Mean rate of change was +0.43 events per hour per year, a 3.3% yearly increase relative to the maximum AHI observed for each case. Within individuals, curve fitting indicated statistically significant AHI increases associated not only with increases, but also decreases, in weight. Conclusions: Rates of increase in AHI were larger than for aging reported for other organ systems (eg, autonomic, musculoskeletal, and respiratory), possibly reflecting complex mechanistic determination of SDB in old age. Association between decreased weight and increased SDB with advancing years represents an important “proof of concept,” perhaps compatible with failure to maintain airway patency during sleep as a component of generalized muscle weakness in old age.

Although we agree with Theobold and Freeman (2014) that linear models are the most appropriate way in which to analyze assessment data, we show the importance of testing for interactions between covariates and factors.