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.

Evidence continues to accrue implicating mitochondrial dysfunction in the etiology of a number of neurodegenerative diseases. For example, Parkinson's disease (PD) can be induced by mitochondrial toxins, and nuclear DNA (nDNA) loci linked to PD have been associated with mitochondrial dysfunction. Although conclusions about the role of mitochondrial DNA (mtDNA) variants in PD vary, we argue here that this is attributable to the novel genetics of the mtDNA and the fact that clinically relevant mtDNA variation encompasses ancient adaptive polymorphisms, recent deleterious mutations, and somatic mutations. An mtDNA association with PD is supported by an analysis of the Russian Tatar population which revealed that polymorphisms associated with haplogroup H mtDNAs increased PD risk (odds ratio [OR]= 2.58, P= 0.0001), whereas those associated with haplogroup UK cluster mtDNAs were protective (OR = 0.38, P= 0.003). Moreover, mtDNA sequencing revealed that PD patients with either haplogroup H or UK cluster mtDNAs can harbor additional recent variants that might further modulate PD risk. Therefore, the complexity of PD genetics may reflect the complex mitochondrial genetics.

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