Ntrk1 mutation co-segregating with bipolar disorder and inherited kidney disease in a multiplex family causes defects in neuronal growth and depression-like behavior in mice

Previously, we reported a family in which bipolar disorder (BD) co-segregates with a Mendelian kidney disorder linked to 1q22. The causative renal gene was later identified as MUC1. Genome-wide linkage analysis of BD in the family yielded a peak at 1q22 that encompassed the NTRK1 and MUC1 genes. NTRK1 codes for TrkA (Tropomyosin-related kinase A) which is essential for development of the cholinergic nervous system. Whole genome sequencing of the proband identified a damaging missense mutation, E492K, in NTRK1. Induced pluripotent stem cells were generated from family members, and then differentiated to neural stem cells (NSCs). E492K NSCs had reduced neurite outgrowth. A conditional knock-in mouse line, harboring the point mutation in the brain, showed depression-like behavior in the tail suspension test following challenge by physostigmine, a cholinesterase inhibitor. These results are consistent with the cholinergic hypothesis of depression. They imply that the NTRK1 E492K mutation, impairs cholinergic neurotransmission, and may convey susceptibility to bipolar disorder.

Integration of genetic and histopathology data in interpretation of kidney disease

For many years renal biopsy has been the gold standard for diagnosis in many forms of kidney disease. It provides rapid, accurate and clinically useful information in most individuals with kidney disease. However, in recent years, other diagnostic modalities have become available that may provide more detailed and specific diagnostic information in addition to, or instead of, renal biopsy. Genomics is one of these modalities. Previously prohibitively expensive and time consuming, it is now increasingly available and practical in a clinical setting for the diagnosis of inherited kidney disease. Inherited kidney disease is a significant cause of kidney disease, in both the adult and paediatric populations. While individual inherited kidney diseases are rare, together they represent a significant burden of disease. Because of the heterogenicity of inherited kidney disease, diagnosis and management can be a challenge and often multiple diagnostic modalities are needed to arrive at a diagnosis. We present updates in genomic medicine for renal disease, how genetic testing integrates with our knowledge of renal histopathology and how the two modalities may interact to enhance patient care.

Disease Modeling To Understand the Pathomechanisms of Human Genetic Kidney Disorders

The class of human genetic kidney diseases is extremely broad and heterogeneous. Accordingly, the range of associated disease phenotypes is highly variable. Many children and adults affected by inherited kidney disease will progress to ESKD at some point in life. Extensive research has been performed on various different disease models to investigate the underlying causes of genetic kidney disease and to identify disease mechanisms that are amenable to therapy. We review some of the research highlights that, by modeling inherited kidney disease, contributed to a better understanding of the underlying pathomechanisms, leading to the identification of novel genetic causes, new therapeutic targets, and to the development of new treatments. We also discuss how the implementation of more efficient genome-editing techniques and tissue-culture methods for kidney research is providing us with personalized models for a precision-medicine approach that takes into account the specificities of the patient and the underlying disease. We focus on the most common model systems used in kidney research and discuss how, according to their specific features, they can differentially contribute to biomedical research. Unfortunately, no definitive treatment exists for most inherited kidney disorders, warranting further exploitation of the existing disease models, as well as the implementation of novel, complex, human patient–specific models to deliver research breakthroughs.