Additive effect of cerebral atrophy on cognition in dementia-free elderly with cerebrovascular disease

Objective: To explore the additive effect of neurodegenerative diseases, measured by atrophy, on neurocognitive function in Asian dementia-free elderly with cerebrovascular disease (CeVD). Methods: The present study employed a cross-sectional design and was conducted between 2010 and 2015 among community-dwelling elderly participants recruited into the study. Eligible participants were evaluated with an extensive neuropsychological battery and neuroimaging. The weighted CeVD burden scale comprising markers of both small- and large-vessel diseases was applied, with a score of ≥2, indicating significant CeVD burden. Cortical atrophy (CA) and medial temporal atrophy (MTA) were graded using the global cortical atrophy scale and Schelten's scale, respectively. Global and domain-specific (attention, executive function, language, visuomotor speed, visuoconstruction, visual memory, and verbal memory) neurocognitive performance was measured using a locally validated neuropsychological battery (Vascular Dementia Battery, VDB). Results: A total of 819 dementia-free participants were included in the analysis. Among none-mild CeVD subjects, there was no significant difference in the global cognitive performance across atrophy groups (no atrophy, CA, and CA+MTA). However, in moderate-severe CeVD subjects, CA+MTA showed significantly worse global cognitive performance compared with those with CA alone (mean difference=-0.35, 95% CI -0.60 to -0.11, p=0.002) and those without atrophy (mean difference=-0.46, 95% CI -0.74 to -0.19, p<0.001, p<0.001). In domain-specific cognitive performance, subjects with CA+MTA performed worse than other groups in visual memory (p=0.005), executive function (p=0.001) and visuomotor speed (p<0.001) in moderate-severe CeVD but not in none-mild CeVD. Conclusions and relevance: Atrophy and moderate-severe CeVD burden showed an additive effect on global and domain-specific cognitive performance. This study highlights the importance of investigating the mechanisms of clinico-pathological interactions between neurodegenerative processes and vascular damage, particularly in the pre-dementia stage

Posterior eye shape measurement with retinal OCT compared to MRI

PURPOSE. Posterior eye shape assessment by magnetic resonance imaging (MRI) is used to study myopia. We tested the hypothesis that optical coherence tomography (OCT), as an alternative, could measure posterior eye shape similarly to MRI. METHODS. Macular spectral-domain OCT and brain MRI images previously acquired as part of the Singapore Epidemiology of Eye Diseases study were analyzed. The right eye in the MRI and OCT images was automatically segmented. Optical coherence tomography segmentations were corrected for optical and display distortions requiring biometry data. The segmentations were fitted to spheres and ellipsoids to obtain the posterior eye radius of curvature (Rc) and asphericity (Qxz). The differences in Rc and Qxz measured by MRI and OCT were tested using paired t-tests. Categorical assignments of prolateness or oblateness using Qxz were compared. RESULTS. Fifty-two subjects (67.8 ± 5.6 years old) with spherical equivalent refraction from +0.50 to -5.38 were included. The mean paired difference between MRI and original OCT posterior eye Rc was 24.03 ± 46.49 mm (P = 0.0005). For corrected OCT images, the difference in Rc decreased to -0.23 ± 2.47 mm (P = 0.51). The difference between MRI and OCT asphericity, Qxz, was -0.052 ± 0.343 (P = 0.28). However, categorical agreement was only moderate (j = 0.50). CONCLUSIONS. Distortion-corrected OCT measurements of Rc and Qxz were not statistically significantly different from MRI, although the moderate categorical agreement suggests that individual differences remained. This study provides evidence that with distortion correction, noninvasive office-based OCT could potentially be used instead of MRI for the study of posterior eye shape

The genetic architecture of type 2 diabetes

The genetic architecture of common traits, including the number, frequency, and effect sizes of inherited variants that contribute to individual risk, has been long debated. Genome-wide association studies have identified scores of common variants associated with type 2 diabetes, but in aggregate, these explain only a fraction of heritability. To test the hypothesis that lower-frequency variants explain much of the remainder, the GoT2D and T2D-GENES consortia performed whole genome sequencing in 2,657 Europeans with and without diabetes, and exome sequencing in a total of 12,940 subjects from five ancestral groups. To increase statistical power, we expanded sample size via genotyping and imputation in a further 111,548 subjects. Variants associated with type 2 diabetes after sequencing were overwhelmingly common and most fell within regions previously identified by genome-wide association studies. Comprehensive enumeration of sequence variation is necessary to identify functional alleles that provide important clues to disease pathophysiology, but large-scale sequencing does not support a major role for lower-frequency variants in predisposition to type 2 diabetes

The genetic architecture of type 2 diabetes

The genetic architecture of common traits, including the number, frequency, and effect sizes of inherited variants that contribute to individual risk, has been long debated. Genome-wide association studies have identified scores of common variants associated with type 2 diabetes, but in aggregate, these explain only a fraction of the heritability of this disease. Here, to test the hypothesis that lower-frequency variants explain much of the remainder, the GoT2D and T2D-GENES consortia performed whole-genome sequencing in 2,657 European individuals with and without diabetes, and exome sequencing in 12,940 individuals from five ancestry groups. To increase statistical power, we expanded the sample size via genotyping and imputation in a further 111,548 subjects. Variants associated with type 2 diabetes after sequencing were overwhelmingly common and most fell within regions previously identified by genome-wide association studies. Comprehensive enumeration of sequence variation is necessary to identify functional alleles that provide important clues to disease pathophysiology, but large-scale sequencing does not support the idea that lower-frequency variants have a major role in predisposition to type 2 diabetes