Detailed phenotypic and genotypic characterization of bietti crystalline dystrophy

OBJECTIVE: To provide a detailed phenotype/genotype characterization of Bietti crystalline dystrophy (BCD). DESIGN: Observational case series. PARTICIPANTS: Twenty patients from 17 families recruited from a multiethnic British population. METHODS: Patients underwent color fundus photography, near-infrared (NIR) imaging, fundus autofluorescence (FAF) imaging, spectral domain optical coherence tomography (SD-OCT), and electroretinogram (ERG) assessment. The gene CYP4V2 was sequenced. MAIN OUTCOME MEASURES: Clinical, imaging, electrophysiologic, and molecular genetics findings. RESULTS: Patients ranged in age from 19 to 72 years (median, 40 years), with a visual acuity of 6/5 to perception of light (median, 6/12). There was wide intrafamilial and interfamilial variability in clinical severity. The FAF imaging showed well-defined areas of retinal pigment epithelium (RPE) loss that corresponded on SD-OCT to well-demarcated areas of outer retinal atrophy. Retinal crystals were not evident on FAF imaging and were best visualized with NIR imaging. Spectral domain OCT showed them to be principally located on or in the RPE/Bruch's membrane complex. Disappearance of the crystals, revealed by serial recording, was associated with severe disruption and thinning of the RPE/Bruch's membrane complex. Cases with extensive RPE degeneration (N = 5) had ERGs consistent with generalized rod and cone dysfunction, but those with more focal RPE atrophy showed amplitude reduction without delay (N = 3), consistent with restricted loss of function, or that was normal (N = 2). Likely disease-causing variants were identified in 34 chromosomes from 17 families. Seven were novel, including p.Met66Arg, found in all 11 patients from 8 families of South Asian descent. This mutation appears to be associated with earlier onset (median age, 30 years) compared with other substitutions (median age, 41 years). Deletions of exon 7 were associated with more severe disease. CONCLUSIONS: The phenotype is highly variable. Several novel variants are reported, including a highly prevalent substitution in patients of South Asian descent that is associated with earlier-onset disease. Autofluorescence showed sharply demarcated areas of RPE loss that coincided with abrupt edges of outer retinal atrophy on SD-OCT; crystals were generally situated on or in the RPE/Bruch's complex but could disappear over time with associated RPE disruption. These results support a role for the RPE in disease pathogenesis.

Preterm nutritional intake and MRI phenotype at term age: a prospective observational study

Objective: To describe (1) the relationship between nutrition and the preterm-at-term infant phenotype, (2) phenotypic differences between preterm-at-term infants and healthy term born infants and (3) relationships between somatic and brain MRI outcomes. Design: Prospective observational study. Setting: UK tertiary neonatal unit. Participants: Preterm infants (<32 weeks gestation) (n=22) and healthy term infants (n=39) Main outcome measures: Preterm nutrient intake; total and regional adipose tissue (AT) depot volumes; brain volume and proximal cerebral arterial vessel tortuosity (CAVT) in preterm infants and in term infants. Results: Preterm nutrition was deficient in protein and high in carbohydrate and fat. Preterm nutrition was not related to AT volumes, brain volume or proximal CAVT score; a positive association was noted between human milk intake and proximal CAVT score (r=0.44, p=0.05). In comparison to term infants, preterm infants had increased total adiposity, comparable brain volumes and reduced proximal CAVT scores. There was a significant negative correlation between deep subcutaneous abdominal AT volume and brain volume in preterm infants (r=−0.58, p=0.01). Conclusions: Though there are significant phenotypic differences between preterm infants at term and term infants, preterm macronutrient intake does not appear to be a determinant. Our preliminary data suggest that (1) human milk may exert a beneficial effect on cerebral arterial vessel tortuosity and (2) there is a negative correlation between adiposity and brain volume in preterm infants at term. Further work is warranted to see if our findings can be replicated and to understand the causal mechanisms.

Validation of a fast method for quantification of intra-abdominal and subcutaneous adipose tissue for large-scale human studies

Central obesity is the hallmark of a number of non-inheritable disorders. The advent of imaging techniques such asMRI has allowed for a fast and accurate assessment of body fat content and distribution. However, image analysis continues to be one of the major obstacles to the use of MRI in large-scale studies. In this study we assess the validity of the recently proposed fat–muscle quantitation system (AMRATM Profiler) for the quantification of intra-abdominal adipose tissue (IAAT) and abdominal subcutaneous adipose tissue (ASAT) from abdominal MR images. Abdominal MR images were acquired from 23 volunteers with a broad range of BMIs and analysed using sliceOmatic, the current gold-standard, and the AMRATM Profiler based on a non-rigid image registration of a library of segmented atlases. The results show that there was a highly significant correlation between the fat volumes generated by the two analysis methods, (Pearson correlation r = 0.97, p < 0.001), with the AMRATM Profiler analysis being significantly faster (~3 min) than the conventional sliceOmatic approach (~40 min). There was also excellent agreement between the methods for the quantification of IAAT (AMRA 4.73 ± 1.99 versus sliceOmatic 4.73 ± 1.75 l, p = 0.97). For the AMRATM Profiler analysis, the intra-observer coefficient of variation was 1.6% for IAAT and 1.1% for ASAT, the inter-observer coefficient of variationwas 1.4%for IAAT and 1.2%for ASAT, the intra-observer correlationwas 0.998 for IAAT and 0.999 for ASAT, and the inter-observer correlation was 0.999 for both IAAT and ASAT. These results indicate that precise and accurate measures of body fat content and distribution can be obtained in a fast and reliable form by the AMRATM Profiler, opening up the possibility of large-scale human phenotypic studies.