Idiopathic intracranial hypertension: the association between weight loss and the requirement for systemic treatment

<p>Abstract</p> <p>Background</p> <p>To determine whether weight loss is significantly associated with a discontinuation of treatment for idiopathic intracranial hypertension</p> <p>Methods</p> <p>The notes of 36 patients with idiopathic intracranial hypertension under regular review for at least 12 months by a single neuro-ophthalmologist were retrospectively reviewed. Weight was recorded at each assessment and weight loss recommended. Treatment was adjusted according to symptoms, visual function including visual fields and optic disc appearance only. Patients were divided according to duration of continuous follow-up, and then sub-divided as to whether they were on or not on treatment at most recent review and whether weight loss had been achieved compared to presentation. Survival analysis was performed to assess the probability of remaining on treatment having lost weight.</p> <p>Results</p> <p>Considering the patients as 3 groups, those with at least 12 months follow-up (n = 36), those with at least 18 months follow-up (n = 24) and those with 24 months or more follow-up (n = 19), only the group with 24 months or more follow-up demonstrated a significant association between weight loss and stopping systemic treatment (Fisher's exact test, p = 0.04). Survival analysis demonstrated that the probability of being on treatment at 5 years having gained weight was 0.63 and having lost weight was 0.38 (log rank test, p = 0.04). The results suggest that final absolute body mass index is more important than the change in body mass index for patients who stop treatment (Mann Whitney U, p = 0.05).</p> <p>Conclusion</p> <p>This is the first study to demonstrate that weight loss is associated with discontinuation of treatment. Unlike previous studies, our results suggest that final absolute body mass index is more important for stopping treatment than a proportional reduction in weight.</p

Association analysis identifies 65 new breast cancer risk loci

Breast cancer risk is influenced by rare coding variants in susceptibility genes, such as BRCA1, and many common, mostly non-coding variants. However, much of the genetic contribution to breast cancer risk remains unknown. Here we report the results of a genome-wide association study of breast cancer in 122,977 cases and 105,974 controls of European ancestry and 14,068 cases and 13,104 controls of East Asian ancestry. We identified 65 new loci that are associated with overall breast cancer risk at P < 5 × 10-8. The majority of credible risk single-nucleotide polymorphisms in these loci fall in distal regulatory elements, and by integrating in silico data to predict target genes in breast cells at each locus, we demonstrate a strong overlap between candidate target genes and somatic driver genes in breast tumours. We also find that heritability of breast cancer due to all single-nucleotide polymorphisms in regulatory features was 2-5-fold enriched relative to the genome-wide average, with strong enrichment for particular transcription factor binding sites. These results provide further insight into genetic susceptibility to breast cancer and will improve the use of genetic risk scores for individualized screening and prevention.We thank all the individuals who took part in these studies and all the researchers, clinicians, technicians and administrative staff who have enabled this work to be carried out. Genotyping of the OncoArray was principally funded from three sources: the PERSPECTIVE project, funded by the Government of Canada through Genome Canada and the Canadian Institutes of Health Research, the ‘Ministère de l’Économie, de la Science et de l’Innovation du Québec’ through Genome Québec, and the Quebec Breast Cancer Foundation; the NCI Genetic Associations and Mechanisms in Oncology (GAME-ON) initiative and Discovery, Biology and Risk of Inherited Variants in Breast Cancer (DRIVE) project (NIH Grants U19 CA148065 and X01HG007492); and Cancer Research UK (C1287/A10118 and C1287/A16563). BCAC is funded by Cancer Research UK (C1287/A16563), by the European Community’s Seventh Framework Programme under grant agreement 223175 (HEALTH-F2-2009-223175) (COGS) and by the European Union’s Horizon 2020 Research and Innovation Programme under grant agreements 633784 (B-CAST) and 634935 (BRIDGES). Genotyping of the iCOGS array was funded by the European Union (HEALTH-F2-2009-223175), Cancer Research UK (C1287/A10710), the Canadian Institutes of Health Research for the ‘CIHR Team in Familial Risks of Breast Cancer’ program, and the Ministry of Economic Development, Innovation and Export Trade of Quebec, grant PSR-SIIRI-701. Combining of the GWAS data was supported in part by The National Institute of Health (NIH) Cancer Post-Cancer GWAS initiative grant U19 CA 148065 (DRIVE, part of the GAME-ON initiative)

Polygenic Risk Scores for Prediction of Breast Cancer and Breast Cancer Subtypes.

Stratification of women according to their risk of breast cancer based on polygenic risk scores (PRSs) could improve screening and prevention strategies. Our aim was to develop PRSs, optimized for prediction of estrogen receptor (ER)-specific disease, from the largest available genome-wide association dataset and to empirically validate the PRSs in prospective studies. The development dataset comprised 94,075 case subjects and 75,017 control subjects of European ancestry from 69 studies, divided into training and validation sets. Samples were genotyped using genome-wide arrays, and single-nucleotide polymorphisms (SNPs) were selected by stepwise regression or lasso penalized regression. The best performing PRSs were validated in an independent test set comprising 11,428 case subjects and 18,323 control subjects from 10 prospective studies and 190,040 women from UK Biobank (3,215 incident breast cancers). For the best PRSs (313 SNPs), the odds ratio for overall disease per 1 standard deviation in ten prospective studies was 1.61 (95%CI: 1.57-1.65) with area under receiver-operator curve (AUC) = 0.630 (95%CI: 0.628-0.651). The lifetime risk of overall breast cancer in the top centile of the PRSs was 32.6%. Compared with women in the middle quintile, those in the highest 1% of risk had 4.37- and 2.78-fold risks, and those in the lowest 1% of risk had 0.16- and 0.27-fold risks, of developing ER-positive and ER-negative disease, respectively. Goodness-of-fit tests indicated that this PRS was well calibrated and predicts disease risk accurately in the tails of the distribution. This PRS is a powerful and reliable predictor of breast cancer risk that may improve breast cancer prevention programs