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SummaryObjectiveLocal field potentials (LFPs) arise from synchronous activation of millions of neurons, producing seemingly consistent waveform shapes and relative synchrony across electrodes. Interictal spikes (IISs) are LFPs associated with epilepsy that are commonly used to guide surgical resection. Recently, changes in neuronal firing patterns observed in the minutes preceding seizure onset were found to be reactivated during postseizure sleep, a process called seizure‐related consolidation (SRC), due to similarities with learning‐related consolidation. Because IISs arise from summed neural activity, we hypothesized that changes in IIS shape and relative synchrony would be observed in the minutes preceding seizure onset and would be reactivated preferentially during postseizure slow‐wave sleep (SWS).MethodsScalp and intracranial recordings were obtained continuously across multiple days from clinical macroelectrodes implanted in patients undergoing treatment for intractable epilepsy. Data from scalp electrodes were used to stage sleep. Data from intracranial electrodes were used to detect IISs using a previously established algorithm. Partial correlations were computed for sleep and wake periods before and after seizures as a function of correlations observed in the minutes preceding seizures. Magnetic resonance imaging (MRI) and computed tomography (CT) scans were co‐registered with electroencephalography (EEG) to determine the location of the seizure‐onset zone (SOZ).ResultsChanges in IIS shape and relative synchrony were observed on a subset of macroelectrodes minutes before seizure onset, and these changes were reactivated preferentially during postseizure SWS. Changes in synchrony were greatest for pairs of electrodes where at least one electrode was located in the SOZ.SignificanceThese data suggest preseizure changes in neural activity and their subsequent reactivation occur across a broad spatiotemporal scale: from single neurons to LFPs, both within and outside the SOZ. The preferential reactivation of seizure‐related changes in IISs during postseizure SWS adds to a growing body of literature suggesting that pathologic neural processes may utilize physiologic mechanisms of synaptic plasticity.

Autosomal dominant polycystic kidney disease (ADPKD) often results in ESRD but with a highly variable course. Mutations to PKD1 or PKD2 cause ADPKD; both loci have high levels of allelic heterogeneity. We evaluated genotype-phenotype correlations in 1119 patients (945 families) from the HALT Progression of PKD Study and the Consortium of Radiologic Imaging Study of PKD Study. The population was defined as: 77.7% PKD1, 14.7% PKD2, and 7.6% with no mutation detected (NMD). Phenotypic end points were sex, eGFR, height–adjusted total kidney volume (htTKV), and liver cyst volume. Analysis of the eGFR and htTKV measures showed that the PKD1 group had more severe disease than the PKD2 group, whereas the NMD group had a PKD2-like phenotype. In both the PKD1 and PKD2 populations, men had more severe renal disease, but women had larger liver cyst volumes. Compared with nontruncating PKD1 mutations, truncating PKD1 mutations associated with lower eGFR, but the mutation groups were not differentiated by htTKV. PKD1 nontruncating mutations were evaluated for conservation and chemical change and subdivided into strong (mutation strength group 2 [MSG2]) and weak (MSG3) mutation groups. Analysis of eGFR and htTKV measures showed that patients with MSG3 but not MSG2 mutations had significantly milder disease than patients with truncating cases (MSG1), an association especially evident in extreme decile populations. Overall, we have quantified the contribution of genic and PKD1 allelic effects and sex to the ADPKD phenotype. Intrafamilial correlation analysis showed that other factors shared by families influence htTKV, with these additional genetic/environmental factors significantly affecting the ADPKD phenotype.

AbstractIntroductionWe describe Alzheimer's Disease Neuroimaging Initiative (ADNI) Biomarker Core progress including: the Biobank; cerebrospinal fluid (CSF) amyloid beta (Aβ1–42), t‐tau, and p‐tau181 analytical performance, definition of Alzheimer's disease (AD) profile for plaque, and tangle burden detection and increased risk for progression to AD; AD disease heterogeneity; progress in standardization; and new studies using ADNI biofluids.MethodsReview publications authored or coauthored by ADNI Biomarker core faculty and selected non‐ADNI studies to deepen the understanding and interpretation of CSF Aβ1–42, t‐tau, and p‐tau181 data.ResultsCSF AD biomarker measurements with the qualified AlzBio3 immunoassay detects neuropathologic AD hallmarks in preclinical and prodromal disease stages, based on CSF studies in non‐ADNI living subjects followed by the autopsy confirmation of AD. Collaboration across ADNI cores generated the temporal ordering model of AD biomarkers varying across individuals because of genetic/environmental factors that increase/decrease resilience to AD pathologies.DiscussionFurther studies will refine this model and enable the use of biomarkers studied in ADNI clinically and in disease‐modifying therapeutic trials.

GH is an important regulator of body growth and composition as well as numerous other metabolic processes. In particular, liver plays a key role in the GH/IGF-I axis, because the majority of circulating “endocrine” IGF-I results from GH-stimulated liver IGF-I production. To develop a better understanding of the role of liver in the overall function of GH, we generated a strain of mice with liver-specific GH receptor (GHR) gene knockout (LiGHRKO mice). LiGHRKO mice had a 90% decrease in circulating IGF-I levels, a 300% increase in circulating GH, and significant changes in IGF binding protein (IGFBP)-1, IGFBP-2, IGFBP-3, IGFBP-5, and IGFBP-7. LiGHRKO mice were smaller than controls, with body length and body weight being significantly decreased in both sexes. Analysis of body composition over time revealed a pattern similar to those found in GH transgenic mice; that is, LiGHRKO mice had a higher percentage of body fat at early ages followed by lower percentage of body fat in adulthood. Local IGF-I mRNA levels were significantly increased in skeletal muscle and select adipose tissue depots. Grip strength was increased in LiGHRKO mice. Finally, circulating levels of leptin, resistin, and adiponectin were increased in LiGHRKO mice. In conclusion, LiGHRKO mice are smaller despite increased local mRNA expression of IGF-I in several tissues, suggesting that liver-derived IGF-I is indeed important for normal body growth. Furthermore, our data suggest that novel GH-dependent cross talk between liver and adipose is important for regulation of adipokines in vivo.

High-frequency oscillations (HFO; gamma: 40–100 Hz, ripples: 100–200 Hz, and fast ripples: 250–500 Hz) have been widely studied in health and disease. These phenomena may serve as biomarkers for epileptic brain; however, a means of differentiating between pathological and normal physiological HFO is essential. We categorized task-induced physiological HFO during periods of HFO induced by a visual or motor task by measuring frequency, duration, and spectral amplitude of each event in single trial time-frequency spectra and compared them to pathological HFO similarly measured. Pathological HFO had higher mean spectral amplitude, longer mean duration, and lower mean frequency than physiological-induced HFO. In individual patients, support vector machine analysis correctly classified pathological HFO with sensitivities ranging from 70–98% and specificities >90% in all but one patient. In this patient, infrequent high-amplitude HFO were observed in the motor cortex just before movement onset in the motor task. This finding raises the possibility that in epileptic brain physiological-induced gamma can assume higher spectral amplitudes similar to those seen in pathologic HFO. This method if automated and validated could provide a step towards differentiating physiological HFO from pathological HFO and improving localization of epileptogenic brain.