Objective:To assess the potential connection between PCDH12 and brain calcifications in a patient carrying a homozygous nonsense variant in PCDH12 and in adult patients with brain calcifications.Methods:We performed a CT scan in 1 child with a homozygous PCDH12 nonsense variant. We screened DNA samples from 53 patients with primary familial brain calcification (PFBC) and 26 patients with brain calcification of unknown cause (BCUC).Results:We identified brain calcifications in subcortical and perithalamic regions in the patient with a homozygous PCDH12 nonsense variant. The calcification pattern was different from what has been observed in PFBC and more similar to what is described in in utero infections. In patients with PFBC or BCUC, we found no protein-truncating variant and 3 rare (minor allele frequency <0.001) PCDH12 predicted damaging missense heterozygous variants in 3 unrelated patients, albeit with no segregation data available.Conclusions:Brain calcifications should be added to the phenotypic spectrum associated with PCDH12 biallelic loss of function, in the context of severe cerebral developmental abnormalities. A putative role for PCDH12 variants remains to be determined in PFBC.

Primary familial brain calcifications (PFBC) compose a rare neurologic condition characterized by a bilateral pattern of hydroxyapatite deposits in basal ganglia, dentate nuclei, and thalamus. PFBC is identified through neuroimaging screenings such as computerized tomography. Patients with PFBC might present a wide variety of neurological symptoms such as mental and motor impairments, often misdiagnosed as Parkinson's disease, schizophrenia, Alzheimer's disease, and migraine. Four genes were confirmed as causative of PFBC: SLC20A2, PDGFB, PDGFRB, and XPR1. Curiously, other studies made occasional links between XPR1 variations or expression changes, in a few neuropsychiatric models. This letter is an assembly on XPR1 variants and expression change pattern data that were published in recent scientific reports, even before the current connection between that gene and brain calcification.

Data of mice with PDGF-B-truncating mutation (Pdgfb ) from different research groups indicate that the malfunction of this protein leads to reduced pericyte recruitment, loss of Blood-Brain Barrier (BBB) integrity and bilateral brain calcification. This makes these mice important models for Primary Brain Calcification and pericyte-BBB correlation studies. The global brain pericyte count is reduced in Pdgfb mice, with higher BBB permeability. We have overlapped the data from other research groups into a figure to further analyze the findings. Calcifications form within midbrain, interbrain, basal forebrain, and pons. Interestingly, these calcification-prone regions have a comparably higher pericyte count and lower BBB leakage in relation to other non-calcifying regions of the Pdgfb mouse (such as the cortex and striatum). A comparatively higher BBB integrity in regions prone to calcification seems paradoxical and indicates that other region-specific changes are the cause of the calcifications.

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Dementia, a syndrome characterized by the progressive deterioration of memory and cognition, arises from different pathologies, with Alzheimer's Disease (AD) its most common cause. Patterns of gene expression during dementia of different etiologies may function as generalist biomarkers of the condition. We used RNA-Seq data from the Allen Dementia and Traumatic Brain Injury Study (ADTBI) to identify differentially expressed genes in brains with dementia. Machine Learning algorithms Decision Trees (DT) and Random Forest (RF) were used to create models to identify dementia samples based on their gene expression profile. Importance analyses were conducted to identify the most relevant genes in each classification model. A total of 1629 differentially expressed (DE) genes were found in brains with the condition. Gene PAN3-AS1 was the only DE gene across more than three brain regions. The artificial intelligence models were capable of identifying correctly up to 92.85% of dementia samples. Our analyses provide interesting insights regarding using brain-specific gene expression profiles as biomarkers of dementia, identifying genes possibly involved with dementia, and guiding future studies in prediction and early identification of the syndrome.