Faster Family-wise Error Control for Neuroimaging with a Parametric Bootstrap

In neuroimaging, hundreds to hundreds of thousands of tests are performed across a set of brain regions or all locations in an image. Recent studies have shown that the most common family-wise error (FWE) controlling procedures in imaging, which rely on classical mathematical inequalities or Gaussian random field theory, yield FWE rates that are far from the nominal level. Depending on the approach used, the FWER can be exceedingly small or grossly inflated. Given the widespread use of neuroimaging as a tool for understanding neurological and psychiatric disorders, it is imperative that reliable multiple testing procedures are available. To our knowledge, only permutation joint testing procedures have been shown to reliably control the FWER at the nominal level. However, these procedures are computationally intensive due to the increasingly available large sample sizes and dimensionality of the images, and analyses can take days to complete. Here, we develop a parametric bootstrap joint testing procedure. The parametric bootstrap procedure works directly with the test statistics, which leads to much faster estimation of adjusted \emph{p}-values than resampling-based procedures while reliably controlling the FWER in sample sizes available in many neuroimaging studies. We demonstrate that the procedure controls the FWER in finite samples using simulations, and present region- and voxel-wise analyses to test for sex differences in developmental trajectories of cerebral blood flow

Double- to Single-Strand Transition Induces Forces and Motion in DNA Origami Nanostructures

The design of dynamic, reconfigurable devices is crucial for the bottom-up construction of artificial biological systems. DNA can be used as an engineering material for the de-novo design of such dynamic devices. A self-assembled DNA origami switch is presented that uses the transition from double- to single-stranded DNA and vice versa to create and annihilate an entropic force that drives a reversible conformational change inside the switch. It is distinctively demonstrated that a DNA single-strand that is extended with 0.34 nm per nucleotide - the extension this very strand has in the double-stranded configuration - exerts a contractive force on its ends leading to large-scale motion. The operation of this type of switch is demonstrated via transmission electron microscopy, DNA-PAINT super-resolution microscopy and darkfield microscopy. The work illustrates the intricate and sometimes counter-intuitive forces that act in nanoscale physical systems that operate in fluids

Disrupted anatomic networks in the 22q11.2 deletion syndrome

AbstractThe 22q11.2 deletion syndrome (22q11DS) is an uncommon genetic disorder with an increased risk of psychosis. Although the neural substrates of psychosis and schizophrenia are not well understood, aberrations in cortical networks represent intriguing potential mechanisms. Investigations of anatomic networks within 22q11DS are sparse. We investigated group differences in anatomic network structure in 48 individuals with 22q11DS and 370 typically developing controls by analyzing covariance patterns in cortical thickness among 68 regions of interest using graph theoretical models. Subjects with 22q11DS had less robust geographic organization relative to the control group, particularly in the occipital and parietal lobes. Multiple global graph theoretical statistics were decreased in 22q11DS. These results are consistent with prior studies demonstrating decreased connectivity in 22q11DS using other neuroimaging methodologies

Evaluation of Neurocognition in Youth with CKD Using a Novel Computerized Neurocognitive Battery

BACKGROUND AND OBJECTIVES: Neurocognitive problems in CKD are well documented; time-efficient methods are needed to assess neurocognition in this population. We performed the first study of the efficient 1-hour Penn Computerized Neurocognitive Battery (CNB) in children and young adults with CKD. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: We administered the Penn CNB cross-sectionally to individuals aged 8-25 years with stage 2-5 CKD (n=92, enrolled from three academic nephrology practices from 2011 to 2014) and matched healthy controls (n=69). We analyzed results from 12 tests in four domains: executive control, episodic memory, complex cognition, and social cognition. All tests measure accuracy and speed; we converted raw scores to age-specific z-scores on the basis of Philadelphia Neurodevelopmental Cohort (n=1790) norms. We analyzed each test in a linear regression with accuracy and speed z-scores as dependent variables and with (1) CKD versus control or (2) eGFR as explanatory variables, adjusted for race, sex, and maternal education. RESULTS: Patients with CKD (mean±SD eGFR, 48±25 ml/min per 1.73 m(2); mean age, 16.3±3.9 years) and controls (mean eGFR, 98±20 ml/min per 1.73 m(2); mean age, 16.0±4.0 years) were similar demographically. CKD participants had lower accuracy than controls in tests of complex cognition, with moderate to large effect sizes: -0.53 (95% confidence interval [95% CI], -0.87 to -0.19) for verbal reasoning, -0.52 (95% CI, -0.83 to -0.22) for nonverbal reasoning, and -0.64 (95% CI, -0.99 to -0.29) for spatial processing. For attention, patients with CKD had lower accuracy (effect size, -0.35 [95% CI, -0.67 to -0.03]) but faster response times (effect size, 0.44 [95% CI, 0.04 to 0.83]) than controls, perhaps reflecting greater impulsivity. Lower eGFR was associated with lower accuracy for complex cognition, facial and visual memory, and emotion identification tests. CONCLUSIONS: CKD is associated with lower accuracy in tests of complex cognition, attention, memory, and emotion identification, which related to eGFR. These findings are consistent with traditional neurocognitive testing in previous studies

Genetic Overlap Profiles of Cognitive Ability in Psychotic and Affective Illnesses::A Multi-Site Study of Multiplex Pedigrees

BACKGROUND: Cognitive impairment is a key feature of psychiatric illness, making cognition an important tool for exploring of the genetics of illness risk. It remains unclear which measures should be prioritized in pleiotropy-guided research. Here, we generate profiles of genetic overlap between psychotic and affective disorders and cognitive measures in Caucasian and Hispanic groups. METHODS: Data were from four samples of extended pedigrees (N = 3046). Coefficient of relationship analyses were used to estimate genetic overlap between illness risk and cognitive ability. Results were meta-analyzed. FINDINGS: Psychosis was characterized by cognitive impairments on all measures with a generalized profile of genetic overlap. General cognitive ability shared greatest genetic overlap with psychosis risk (average Endophenotype Ranking Value (ERV) across samples from a random-effects meta-analysis = 0.32) followed by Verbal Memory (ERV = 0.24), Executive Function (ERV = 0.22), and Working Memory (ERV = 0.21). For bipolar disorder, there was genetic overlap with Processing Speed (ERV = 0.05) and Verbal Memory (ERV = 0.11), but these were confined to select samples. Major depression was characterized by enhanced Working and Face Memory performance, as reflected in significant genetic overlap in two samples. INTERPRETATION: There is substantial genetic overlap between risk for psychosis and a range of cognitive abilities (including general intelligence). Most of these effects are largely stable across of ascertainment strategy and ethnicity. Genetic overlap between affective disorders and cognition, on the other hand, tend to be specific to ascertainment strategy, ethnicity, and cognitive test battery

Mental disorders of known aetiology and precision medicine in psychiatry: a promising but neglected alliance [Editorial]

Personalized or precision medicine is predicated on the assumption that the average response to treatment is not necessarily representative of the response of each individual. A commitment to personalized medicine demands an effort to bring evidence-based medicine and personalized medicine closer together. The use of relatively homogeneous groups, defined using a priori criteria, may constitute a promising initial step for developing more accurate risk-prediction models with which to advance the development of personalized evidence-based medicine approaches to heterogeneous syndromes such as schizophrenia. However, this can lead to a paradoxical situation in the field of psychiatry. Since there has been a tendency to loosely define psychiatric disorders as ones without a known aetiology, the discovery of an aetiology for psychiatric syndromes (e.g. 22q11.2 deletion syndrome in some cases of schizophrenia), while offering a path toward more precise treatments, may also lead to their reclassification away from psychiatry. We contend that psychiatric disorders with a known aetiology should not be removed from the field of psychiatry. This knowledge should be used instead to guide treatment, inasmuch as psychotherapies, pharmacotherapies and other treatments can all be valid approaches to mental disorders. The translation of the personalized clinical approach inherent to psychiatry into evidence-based precision medicine can lead to the development of novel treatment options for mental disorders and improve outcomes