Objective: Quantification of gait with wearable technology is promising; recent cross-sectional studies showed that gait characteristics are potential prodromal markers for Parkinson disease (PD). The aim of this longitudinal prospective observational study was to establish gait impairments and trajectories in the prodromal phase of PD, identifying which gait characteristics are potentially early diagnostic markers of PD. Methods: The 696 healthy controls (mean age = 63 AE 7 years) recruited in the Tubingen Evaluation of Risk Factors for Early Detection of Neurodegeneration study were included. Assessments were performed longitudinally 4 times at 2-year intervals, and people who converted to PD were identified. Participants were asked to walk at different speeds under single and dual tasking, with a wearable device placed on the lower back; 14 validated clinically relevant gait characteristics were quantified. Cox regression was used to examine whether gait at first visit could predict time to PD conversion after controlling for age and sex. Random effects linear mixed models (RELMs) were used to establish longitudinal trajectories of gait and model the latency between impaired gait and PD diagnosis. Results: Sixteen participants were diagnosed with PD on average 4.5 years after first visit (converters; PDC). Higher step time variability and asymmetry of all gait characteristics were associated with a shorter time to PD diagnosis. RELMs indicated that gait (lower pace) deviates from that of non-PDC approximately 4 years prior to diagnosis. Interpretation: Together with other prodromal markers, quantitative gait characteristics can play an important role in identifying prodromal PD and progression within this phase.

Repetitive thinking styles such as rumination are considered to be a key factor in the development and maintenance of mental disorders. Different situational triggers (e.g., social stressors) have been shown to elicit rumination in subjects exhibiting such habitual thinking styles. At the same time, the process of rumination influences the adaption to stressful situations. The study at hand aims to investigate the effect of trait rumination on neuronal activation patterns during the Trier Social Stress Test (TSST) as well as the physiological and affective adaptation to this high-stress situation.MethodsA sample of 23 high and 22 low ruminators underwent the TSST and two control conditions while their cortical hemodynamic reactions were measured with functional near-infrared spectroscopy (fNIRS). Additional behavioral, physiological and endocrinological measures of the stress response were assessed.ResultsSubjects showed a linear increase from non-stressful control conditions to the TSST in cortical activity of the cognitive control network (CCN) and dorsal attention network (DAN), comprising the bilateral dorsolateral prefrontal cortex (dlPFC), inferior frontal gyrus (IFG) and superior parietal cortex/somatosensory association cortex (SAC). During stress, high ruminators showed attenuated cortical activity in the right IFG, whereby deficits in IFG activation mediated group differences in post-stress state rumination and negative affect.ConclusionsAberrant activation of the CCN and DAN during social stress likely reflects deficits in inhibition and attention with corresponding negative emotional and cognitive consequences. The results shed light on possible neuronal underpinnings by which high trait rumination may act as a risk factor for the development of clinical syndromes.

The MDS prodromal criteria provide a practical framework for the calculation of prodromal PD risk. Although specificity of the criteria is high, most patients will not meet the criteria before diagnosis unless testing is thoroughly performed with numerous and highly specific markers objectively assessed. © 2017 International Parkinson and Movement Disorder Society.

IMPORTANCE The overall low survival rate of patients with lung cancer calls for improved detection tools to enable better treatment options and improved patient outcomes. Multivariable molecular signatures, such as blood-borne microRNA (miRNA) signatures, may have high rates of sensitivity and specificity but require additional studies with large cohorts and standardized measurements to confirm the generalizability of miRNA signatures.OBJECTIVE To investigate the use of blood-borne miRNAs as potential circulating markers for detecting lung cancer in an extended cohort of symptomatic patients and control participants. DESIGN, SETTING, AND PARTICIPANTSThis multicenter, cohort study included patients from case-control and cohort studies (TREND and COSYCONET) with 3102 patients being enrolled by convenience sampling between March 3, 2009, and March 19, 2018. For the cohort study TREND, population sampling was performed. Clinical diagnoses were obtained for 3046 patients (606 patients with non-small cell and small cell lung cancer, 593 patients with nontumor lung diseases, 883 patients with diseases not affecting the lung, and 964 unaffected control participants). No samples were removed because of experimental issues. The collected data were analyzed between April 2018 and November 2019. MAIN OUTCOMES AND MEASURESSensitivity and specificity of liquid biopsy using miRNA signatures for detection of lung cancer.RESULTS A total of 3102 patients with a mean (SD) age of 61.1 (16.2) years were enrolled. Data on the sex of the participants were available for 2856 participants; 1727 (60.5%) were men. Genome-wide miRNA profiles of blood samples from 3046 individuals were evaluated by machine-learning methods. Three classification scenarios were investigated by splitting the samples equally into training and validation sets. First, a 15-miRNA signature from the training set was used to distinguish patients diagnosed with lung cancer from all other individuals in the validation set with an accuracy of 91.4% (95% CI, 91.0%-91.9%), a sensitivity of 82.8% (95% CI, 81.5%-84.1%), and a specificity of 93.5% (95% CI, 93.2%-93.8%). Second, a 14-miRNA signature from the training set was used to distinguish patients with lung cancer from patients with nontumor lung diseases in the validation set with an accuracy of 92.5% (95% CI, 92.1%-92.9%), sensitivity of 96.4% (95% CI, 95.9%-96.9%), and specificity of 88.6% (95% CI, 88.1%-89.2%). Third, a 14-miRNA signature from the training set was used to distinguish patients with early-stage lung cancer from all individuals without lung cancer in the validation set with an accuracy of 95.9% (95% CI, 95.7%-96.2%), sensitivity of 76.3% (95% CI, 74.5%-78.0%), and specificity of 97.5% (95% CI, 97.2%-97.7%). CONCLUSIONS AND RELEVANCEThe findings of the study suggest that the identified patterns of miRNAs may be used as a component of a minimally invasive lung cancer test, complementing imaging, sputum cytology, and biopsy tests.

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Depression has been shown to be related to a variety of aberrant brain functions and structures. Particularly the investigation of alterations in functional connectivity (FC) in major depressive disorder (MDD) has been a promising endeavor, since a better understanding of pathological brain networks may foster our understanding of the disease. However, the underling mechanisms of aberrant FC in MDD are largely unclear. Using functional near-infrared spectroscopy (fNIRS) we investigated FC in the cortical parts of the default mode network (DMN) during resting-state in patients with current MDD. Additionally, we used qualitative and quantitative measures of psychological processes (e.g., state/trait rumination, mind-wandering) to investigate their contribution to differences in FC between depressed and non-depressed subjects. Our results indicate that 40% of the patients report spontaneous rumination during resting-state. Depressed subjects showed reduced FC in parts of the DMN compared to healthy controls. This finding was linked to the process of state/trait rumination. While rumination was negatively correlated with FC in the cortical parts of the DMN, mind-wandering showed positive associations.

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