No association between polymorphisms in the BDNF gene and age at onset in Huntington disease

BACKGROUND: Recent evidence suggests that brain-derived neurotrophic factor (BDNF) is an attractive candidate for modifying age at onset (AO) in Huntington disease (HD). In particular, the functional Val66Met polymorphism appeared to exert a significant effect. Here we evaluate BDNF variability with respect to AO of HD using markers that represent the entire locus. METHODS: Five selected tagging polymorphisms were genotyped across a 65 kb region comprising the BDNF gene in a well established cohort of 250 unrelated German HD patients. RESULTS: Addition of BDNF genotype variations or one of the marker haplotypes to the effect of CAG repeat lengths did not affect the variance of the AO. CONCLUSION: We were unable to verify a recently reported association between the functional Val66Met polymorphism in the BDNF gene and AO in HD. From our findings, we conclude that neither sequence variations in nor near the gene contribute significantly to the variance of AO

Deep learning enables genetic analysis of the human thoracic aorta

Genome-wide association analyses identify variants associated with thoracic aortic diameter. A polygenic score for ascending aortic diameter was associated with a diagnosis of thoracic aortic aneurysm in independent samples. Enlargement or aneurysm of the aorta predisposes to dissection, an important cause of sudden death. We trained a deep learning model to evaluate the dimensions of the ascending and descending thoracic aorta in 4.6 million cardiac magnetic resonance images from the UK Biobank. We then conducted genome-wide association studies in 39,688 individuals, identifying 82 loci associated with ascending and 47 with descending thoracic aortic diameter, of which 14 loci overlapped. Transcriptome-wide analyses, rare-variant burden tests and human aortic single nucleus RNA sequencing prioritized genes including SVIL, which was strongly associated with descending aortic diameter. A polygenic score for ascending aortic diameter was associated with thoracic aortic aneurysm in 385,621 UK Biobank participants (hazard ratio = 1.43 per s.d., confidence interval 1.32-1.54, P = 3.3 x 10(-20)). Our results illustrate the potential for rapidly defining quantitative traits with deep learning, an approach that can be broadly applied to biomedical images