Nonmotor disturbances in Parkinson's disease

Nonmotor disturbances (NMDs) affect most patients with Parkinson's disease (PD) and often have a profound impact on their quality of life. NMDs such as depression, anxiety, fatigue, REM sleep behavior disorder, constipation, delayed gastric emptying, altered olfaction and pain can precede the onset of motor symptoms. Other NMDs, including hallucinations, dementia, excessive daytime sleepiness, insomnia, orthostatic hypotension and bladder disturbances, typically appear later in the course of PD. For most NMDs of PD, nondopaminergic and non-nigrostriatal mechanisms (e.g. neurodegeneration of other transmitter systems in the cortex and brainstem, side effects of medications, genetic and psychosocial factors) are considered more relevant than the 'classical' dopaminergic-nigrostriatal dysfunction. The recognition of NMDs requires a high degree of clinical suspicion, the use of specific questionnaires and ancillary tests. Pharmacological and nonpharmacological approaches can be effective, but for most forms of treatment of NMDs, the scientific evidence is limited

Analysis of shared heritability in common disorders of the brain

Disorders of the brain can exhibit considerable epidemiological comorbidity and often share symptoms, provoking debate about their etiologic overlap. We quantified the genetic sharing of 25 brain disorders from genome-wide association studies of 265,218 patients and 784,643 control participants and assessed their relationship to 17 phenotypes from 1,191,588 individuals. Psychiatric disorders share common variant risk, whereas neurological disorders appear more distinct from one another and from the psychiatric disorders. We also identified significant sharing between disorders and a number of brain phenotypes, including cognitive measures. Further, we conducted simulations to explore how statistical power, diagnostic misclassification, and phenotypic heterogeneity affect genetic correlations. These results highlight the importance of common genetic variation as a risk factor for brain disorders and the value of heritability-based methods in understanding their etiology