Data-Driven Phenotypic Categorization for Neurobiological Analyses: Beyond DSM-5 Labels.

BACKGROUND: Data-driven approaches can capture behavioral and biological variation currently unaccounted for by contemporary diagnostic categories, thereby enhancing the ability of neurobiological studies to characterize brain-behavior relationships. METHODS: A community-ascertained sample of individuals (N = 347, 18-59 years of age) completed a battery of behavioral measures, psychiatric assessment, and resting-state functional magnetic resonance imaging in a cross-sectional design. Bootstrap-based exploratory factor analysis was applied to 49 phenotypic subscales from 10 measures. Hybrid hierarchical clustering was applied to resultant factor scores to identify nested groups. Adjacent groups were compared via independent samples t tests and chi-square tests of factor scores, syndrome scores, and psychiatric prevalence. Multivariate distance matrix regression examined functional connectome differences between adjacent groups. RESULTS: Reduction yielded six factors, which explained 77.8% and 65.4% of the variance in exploratory and constrained exploratory models, respectively. Hybrid hierarchical clustering of these six factors identified two, four, and eight nested groups (i.e., phenotypic communities). At the highest clustering level, the algorithm differentiated functionally adaptive and maladaptive groups. At the middle clustering level, groups were separated by problem type (maladaptive groups; internalizing vs. externalizing problems) and behavioral type (adaptive groups; sensation-seeking vs. extraverted/emotionally stable). Unique phenotypic profiles were also evident at the lowest clustering level. Group comparisons exhibited significant differences in intrinsic functional connectivity at the highest clustering level in somatomotor, thalamic, basal ganglia, and limbic networks. CONCLUSIONS: Data-driven approaches for identifying homogenous subgroups, spanning typical function to dysfunction, not only yielded clinically meaningful groups, but also captured behavioral and neurobiological variation among healthy individuals.

Actividad funcional cerebral en estado de reposo: redes en conexión / Functional cerebral activity in a state of rest: connectivity networks

El análisis de la conectividad funcional mediante resonancia magnética funcional (RMf) puede llevarse a cabo durante la realización de una tarea, la percepción de un estímulo o en estado de reposo. En tales casos, el estudio de la señal de baja frecuencia en la actividad cerebral a través del contraste BOLD en estado de reposo ha revelado patrones de actividad cortical sincronizados, lo que ha permitido describir la arquitectura funcional intrínseca del cerebro humano. La comunidad científica internacional dispone de recursos compartidos que contribuirán mediante este análisis de RMf en estado de reposo a la obtención de diagnósticos y tratamientos más precisos y avanzados en el campo de las neurociencias. Recientemente, el Spanish Resting State Network (SRSN) se ha aunado a este proyecto colaborativo creando una estructura de habla española para la cooperación entre los distintos grupos de investigación en neurociencias (http:// www.nitrc.org/projects/srsn)(AU)

Functional connectivity can be measured during task-based functional magnetic resonance imaging (fMRI), or in the absence of specific stimuli or tasks. In either case, the study of low frequency fluctuations in the BOLD signal reveals patterns of synchronization which delineate the intrinsic functional architecture of the brain. The scientific community now has available shared resources to accelerate the exploitation of resting state fMRI with the objectives of improving diagnostic methods and leading to better treatments grounded in neuroscience. Fomenting a collaborative scientific culture will accelerate our understanding of the underlying phenonmemna. Recently, the Spanish Resting State Network (SRSN) has joined this collaborative effort by creating a setting to facilitate collaboration among the various neuroscience research groups working in Spanish (http://www.nitrc.org/projects/srsn) (AU)

Hacia un entendimiento de los mecanismos moleculares de los tratamientos farmacológicos del trastorno por déficit de atención/hiperactividad / Towards an understanding of the molecular mechanisms underlying the pharmacological treatments of attention deficit hyperactivity disorder

El metilfenidato y las anfetaminas son los fármacos más utilizados para el tratamiento del trastorno por déficit de atención/hiperactividad (TDAH). Estos fármacos modulan la noradrenalina tanto como la dopamina. El metilfenidato funciona únicamente como bloqueador de los transportadores de noradrenalina y dopamina. Las anfetaminas tienen este mismo efecto, pero, además, producen la liberación de noradrenalina, dopamina y serotonina desde las vesículas neuronales presinápticas. Las anfetaminas son más eficientes en aumentar los niveles sinápticos de dopamina, al no requerir que las neuronas estén activadas para producir la liberación de neurotransmisores. Los aumentos de dopamina producidos por estos fármacos se han identificado en el estriato en seres humanos; sin embargo, es probable que los efectos de los fármacos sean también importantes en otros circuitos cerebrales, particularmente en la corteza prefrontal. El bloqueo del transportador de noradrenalina en circuitos de la corteza prefrontal también aumenta los niveles de dopamina. Adicionalmente, se considera que algunos efectos importantes noradrenérgicos son mediados por receptores del subtipo alfa-2a. Un estudio recientemente hecho en primates mostró que el metilfenidato y la atomoxetina aumentaron la eficiencia de las neuronas piramidales, pero a través de diferentes mecanismos. El metilfenidato disminuye señales no específicas a través de receptores dopaminérgicos del tipo D1. En contraste, la atomoxetina incrementa la amplitud de las señales específicamente relacionadas con la función de la neurona particular, a través de receptores alfa-2a. Este hallazgo, aunque en primates, implica que el uso de combinaciones de agentes actuando de manera complementaria en los receptores D1 y alfa-2a debería considerarse y evaluarse de manera rigurosa en pacientes con TDAH que no responden suficientemente bien a tratamiento con un solo fármaco (AU)

Methylphenidate and the amphetamines are the most frequently used medications for treating attentiondeficit/ hyperactivity disorder (ADHD). These medications modulate both norepinephrine as well as dopamine. Methyl phenidate is a pure blocker of the norepinephrine and dopamine transporters. The amphetamines also block reuptake of both catecholamines, but they also release all three monoamines, norepinephrine, dopamine, and serotonin, from presynaptic vesicles. Amphetamines are the most robust agents in increasing synaptic dopamine levels, since they do so regardless of the endogenous level of the relevant neurons. Stimulant-evoked synaptic increases of dopamine have been demonstrated in the striatum in humans, but pharmacologic effects are likely relevant to therapeutic action in other regions, particularly the prefrontal cortex. Blockade of noradrenergic reuptake in the prefrontal cortex may also indirectly increase prefrontal dopamine levels, but there is also evidence that noradrenergic effects are mediated by alpha-2a noradrenergic receptors. A recent study in non-human primates found that methylphenidate and atomoxetine both increased the efficiency of prefrontal pyramidal neurons, but via distinct mechanisms. Methylphenidate decreased non-specific signals, i.e., neuronal noise, via D1 receptors. By contrast, atomoxetine increased the strength of specific signals via activation of alpha-2 receptors. These findings, although in non-human primates, suggest that combinations of agents working on these complementary systems (D1 and alpha-2a) may be worth considering and evaluating rigorously in patients with ADHD with sub-optimal responses to monotherapy (AU)