Abstract Background Epidemiological survey studies have suggested that a large fraction of the adult population, from five to more than 10%, have symptoms of Restless Legs Syndrome (RLS). Recently, ...however, it has become clear that the positive predictive value of many questionnaire screens for RLS may be fairly low and that many individuals who are identified by these screens have other conditions that can “mimic” the features of RLS by satisfying the four diagnostic criteria. We noted the presence of such confounders in a case-control family study and sought to develop methods to differentiate them from true RLS. Methods Family members from the case-control study were interviewed blindly by an RLS expert using the validated Hopkins telephone diagnostic interview (HTDI). Besides questions on the four key diagnostic features of RLS, the HTDI contains open-ended questions on symptom quality and relief strategies and other questions to probe the character of provocative situations and modes of relief. Based on the entire HDTI, a diagnosis of definite, probable or possible RLS or Not-RLS was made. Results Out of 1255 family members contacted, we diagnosed 1232: 402 (32.0%) had definite or probable RLS, 42 (3.3%) possible RLS, and 788 (62.8%) Not-RLS. Of the 788 family members who were determined not to have RLS, 126 could satisfy all four diagnostic criteria (16%). This finding indicates that the specificity of the four criteria was only 84%. Those with mimic conditions were found to have atypical presentations whose features could be used to assist in final diagnosis. Conclusion A variety of conditions, including cramps, positional discomfort, and local leg pathology can satisfy all four diagnostic criteria for RLS and thereby “mimic” RLS by satisfying the four diagnostic criteria. Definitive diagnosis of RLS, therefore, requires exclusion of these other conditions, which may be more common in the population than true RLS. Short of an extended clinical interview and workup, certain features of presentation help differentiate mimics from true RLS.
Restless legs syndrome produces significant chronic sleep loss, which despite not causing expected profound sleepiness, might nonetheless produce cognitive deficits similar to those seen with acute ...sleep deprivation, i.e. involving mostly pre-frontal cortical (PFC) functioning.
Sixteen patients off RLS treatment for at least 2 weeks and 15 age- and gender-matched control subjects had polysomnograms (PSGs) on two consecutive nights. Cognitive tests were given in the morning after the second night. Six cognitive tests were used: two Verbal Fluency tests and the Trail Making tests were selected to be particularly sensitive to PFC function and sleep loss. Porteus Mazes and the Stroop Test were selected to reflect more general frontal and executive function. The Colored Progressive Matrices were used to assess general cognitive skills.
RLS patients compared to controls showed significant (
P<0.05) and sizeable (20–40%) deficits on two of the three PFC tests and marginally non-significant deficit (
P<0.1) on the third. The other three tests showed no significant differences.
The results indicate that RLS patients show cognitive deficits similar to that reported for one night of sleep loss.
To determine if recently abstinent, heavy marijuana (MJ) users show differences in polysomnographic (PSG) measures compared with a drug-free control group.
A group of carefully selected heavy MJ ...users were chosen for study inclusion and matched to a drug-free control group. Questionnaire data were collected prior to cessation of MJ use. PSG studies were conducted during 2 consecutive nights after discontinuation of MJ use in our core sleep laboratory.
Baltimore Maryland, General Clinical Research Center (GCRC) core sleep lab.
17 heavy MJ users discontinuing MJ use and 14 drug-free controls. Men and women were studied, 18 to 30 years. The MJ users reported no other drug use and alcohol use was negligible in both groups. Urine was positive for metabolites of cannabis only.
The MJ users showed differences in PSG measures (lower total sleep times, and less slow wave sleep than the control group) on both nights; they also showed worse sleep efficiency, longer sleep onset, and shorter REM latency than the control group on Night 2. More sleep continuity parameters were significantly worse for the MJ group than the control group on Night 2 versus Night 1, indicating that sleep in the MJ group was relatively worse on Night 2 compared to Night 1. The MJ group did not show improved sleep after an adaptation night as expected. Withdrawal symptoms, craving, and depression did not appear to influence these findings.
During discontinuation of heavy MJ use, PSG measures of sleep disturbance were detected in MJ users compared with a drug-free control group. While this preliminary study cannot identify the extent to which these group differences were present before abstinence, poor sleep quality either prior to or after MJ discontinuation could result in treatment failure for MJ users. Further investigation is necessary to determine the association between the use and cessation of MJ and sleep disturbance.
Abstract Background Abrupt discontinuation of heavy marijuana (MJ) use is associated with self-reports of sleep difficulty. Disturbed sleep is clinically important because MJ users experiencing sleep ...problems may relapse to MJ use to improve their sleep quality. Few studies have used polysomnography (PSG) to characterize changes in sleep architecture during abrupt abstinence from heavy MJ use. Methods We recorded PSG measures on nights 1, 2, 7, 8, and 13 after abrupt MJ discontinuation in 18 heavy MJ users residing in an inpatient unit. Results Across abstinence, Total Sleep Time (TST), Sleep Efficiency (SEff), and amount of REM sleep declined, while Wake after Sleep Onset (WASO) and Periodic Limb Movements (PLM) increased. Furthermore, quantity (joints/week) and duration (years) of MJ use were positively associated with more PLMs. Conclusion The treatment of sleep disturbance is a potential target for the management of cannabis use disorders since poor sleep could contribute to treatment failure in heavy MJ users.
Parkinson's disease is a genetically complex disorder. Multiple genes have been shown to contribute to the risk of Parkinson's disease, and currently 90 independent risk variants have been identified ...by genome-wide association studies. Thus far, a number of genes (including SNCA, LRRK2, and GBA) have been shown to contain variability across a spectrum of frequency and effect, from rare, highly penetrant variants to common risk alleles with small effect sizes. Variants in GBA, encoding the enzyme glucocerebrosidase, are associated with Lewy body diseases such as Parkinson's disease and Lewy body dementia. These variants, which reduce or abolish enzymatic activity, confer a spectrum of disease risk, from 1.4- to >10-fold. An outstanding question in the field is what other genetic factors that influence GBA-associated risk for disease, and whether these overlap with known Parkinson's disease risk variants. Using multiple, large case-control datasets, totalling 217 165 individuals (22 757 Parkinson's disease cases, 13 431 Parkinson's disease proxy cases, 622 Lewy body dementia cases and 180 355 controls), we identified 1691 Parkinson's disease cases, 81 Lewy body dementia cases, 711 proxy cases and 7624 controls with a GBA variant (p.E326K, p.T369M or p.N370S). We performed a genome-wide association study and analysed the most recent Parkinson's disease-associated genetic risk score to detect genetic influences on GBA risk and age at onset. We attempted to replicate our findings in two independent datasets, including the personal genetics company 23andMe, Inc. and whole-genome sequencing data. Our analysis showed that the overall Parkinson's disease genetic risk score modifies risk for disease and decreases age at onset in carriers of GBA variants. Notably, this effect was consistent across all tested GBA risk variants. Dissecting this signal demonstrated that variants in close proximity to SNCA and CTSB (encoding cathepsin B) are the most significant contributors. Risk variants in the CTSB locus were identified to decrease mRNA expression of CTSB. Additional analyses suggest a possible genetic interaction between GBA and CTSB and GBA p.N370S induced pluripotent cell-derived neurons were shown to have decreased cathepsin B expression compared to controls. These data provide a genetic basis for modification of GBA-associated Parkinson's disease risk and age at onset, although the total contribution of common genetics variants is not large. We further demonstrate that common variability at genes implicated in lysosomal function exerts the largest effect on GBA associated risk for disease. Further, these results have implications for selection of GBA carriers for therapeutic interventions.
A key driver of patients' well-being and clinical trials for Parkinson's disease (PD) is the course that the disease takes over time (progression and prognosis). To assess how genetic variation ...influences the progression of PD over time to dementia, a major determinant for quality of life, we performed a longitudinal genome-wide survival study of 11.2 million variants in 3,821 patients with PD over 31,053 visits. We discover RIMS2 as a progression locus and confirm this in a replicate population (hazard ratio (HR) = 4.77, P = 2.78 × 10
), identify suggestive evidence for TMEM108 (HR = 2.86, P = 2.09 × 10
) and WWOX (HR = 2.12, P = 2.37 × 10
) as progression loci, and confirm associations for GBA (HR = 1.93, P = 0.0002) and APOE (HR = 1.48, P = 0.001). Polygenic progression scores exhibit a substantial aggregate association with dementia risk, while polygenic susceptibility scores are not predictive. This study identifies a novel synaptic locus and polygenic score for cognitive disease progression in PD and proposes diverging genetic architectures of progression and susceptibility.
Recent genome-wide association studies (GWAS) and pathway analyses supported long-standing observations of an association between immune-mediated diseases and Parkinson disease (PD). The post-GWAS ...era provides an opportunity for cross-phenotype analyses between different complex phenotypes.
To test the hypothesis that there are common genetic risk variants conveying risk of both PD and autoimmune diseases (ie, pleiotropy) and to identify new shared genetic variants and their pathways by applying a novel statistical framework in a genome-wide approach.
Using the conjunction false discovery rate method, this study analyzed GWAS data from a selection of archetypal autoimmune diseases among 138 511 individuals of European ancestry and systemically investigated pleiotropy between PD and type 1 diabetes, Crohn disease, ulcerative colitis, rheumatoid arthritis, celiac disease, psoriasis, and multiple sclerosis. NeuroX data (6927 PD cases and 6108 controls) were used for replication. The study investigated the biological correlation between the top loci through protein-protein interaction and changes in the gene expression and methylation levels. The dates of the analysis were June 10, 2015, to March 4, 2017.
The primary outcome was a list of novel loci and their pathways involved in PD and autoimmune diseases.
Genome-wide conjunctional analysis identified 17 novel loci at false discovery rate less than 0.05 with overlap between PD and autoimmune diseases, including known PD loci adjacent to GAK, HLA-DRB5, LRRK2, and MAPT for rheumatoid arthritis, ulcerative colitis and Crohn disease. Replication confirmed the involvement of HLA, LRRK2, MAPT, TRIM10, and SETD1A in PD. Among the novel genes discovered, WNT3, KANSL1, CRHR1, BOLA2, and GUCY1A3 are within a protein-protein interaction network with known PD genes. A subset of novel loci was significantly associated with changes in methylation or expression levels of adjacent genes.
The study findings provide novel mechanistic insights into PD and autoimmune diseases and identify a common genetic pathway between these phenotypes. The results may have implications for future therapeutic trials involving anti-inflammatory agents.
Summary Background Cognitive decline is a debilitating manifestation of disease progression in Parkinson's disease. We aimed to develop a clinical–genetic score to predict global cognitive impairment ...in patients with the disease. Methods In this longitudinal analysis, we built a prediction algorithm for global cognitive impairment (defined as Mini Mental State Examination MMSE ≤25) using data from nine cohorts of patients with Parkinson's disease from North America and Europe assessed between 1986 and 2016. Candidate predictors of cognitive decline were selected through a backward eliminated Cox's proportional hazards analysis using the Akaike's information criterion. These were used to compute the multivariable predictor on the basis of data from six cohorts included in a discovery population. Independent replication was attained in patients from a further three independent longitudinal cohorts. The predictive score was rebuilt and retested in 10 000 training and test sets randomly generated from the entire study population. Findings 3200 patients with Parkinson's disease who were longitudinally assessed with 27 022 study visits between 1986 and 2016 in nine cohorts from North America and Europe were assessed for eligibility. 235 patients with MMSE ≤25 at baseline and 135 whose first study visit occurred more than 12 years from disease onset were excluded. The discovery population comprised 1350 patients (after further exclusion of 334 with missing covariates) from six longitudinal cohorts with 5165 longitudinal visits over 12·8 years (median 2·8, IQR 1·6–4·6). Age at onset, baseline MMSE, years of education, motor exam score, sex, depression, and β-glucocerebrosidase ( GBA ) mutation status were included in the prediction model. The replication population comprised 1132 patients (further excluding 14 patients with missing covariates) from three longitudinal cohorts with 19 127 follow-up visits over 8·6 years (median 6·5, IQR 4·1–7·2). The cognitive risk score predicted cognitive impairment within 10 years of disease onset with an area under the curve (AUC) of more than 0·85 in both the discovery (95% CI 0·82–0·90) and replication (95% CI 0·78–0·91) populations. Patients scoring in the highest quartile for cognitive risk score had an increased hazard for global cognitive impairment compared with those in the lowest quartile (hazard ratio 18·4 95% CI 9·4–36·1). Dementia or disabling cognitive impairment was predicted with an AUC of 0·88 (95% CI 0·79–0·94) and a negative predictive value of 0·92 (95% 0·88–0·95) at the predefined cutoff of 0·196. Performance was stable in 10 000 randomly resampled subsets. Interpretation Our predictive algorithm provides a potential test for future cognitive health or impairment in patients with Parkinson's disease. This model could improve trials of cognitive interventions and inform on prognosis. Funding National Institutes of Health, US Department of Defense.
Dementia with Lewy bodies is the second most common form of dementia in elderly people but has been overshadowed in the research field, partly because of similarities between dementia with Lewy ...bodies, Parkinson's disease, and Alzheimer's disease. So far, to our knowledge, no large-scale genetic study of dementia with Lewy bodies has been done. To better understand the genetic basis of dementia with Lewy bodies, we have done a genome-wide association study with the aim of identifying genetic risk factors for this disorder.
In this two-stage genome-wide association study, we collected samples from white participants of European ancestry who had been diagnosed with dementia with Lewy bodies according to established clinical or pathological criteria. In the discovery stage (with the case cohort recruited from 22 centres in ten countries and the controls derived from two publicly available database of Genotypes and Phenotypes studies phs000404.v1.p1 and phs000982.v1.p1 in the USA), we performed genotyping and exploited the recently established Haplotype Reference Consortium panel as the basis for imputation. Pathological samples were ascertained following autopsy in each individual brain bank, whereas clinical samples were collected after participant examination. There was no specific timeframe for collection of samples. We did association analyses in all participants with dementia with Lewy bodies, and also only in participants with pathological diagnosis. In the replication stage, we performed genotyping of significant and suggestive results from the discovery stage. Lastly, we did a meta-analysis of both stages under a fixed-effects model and used logistic regression to test for association in each stage.
This study included 1743 patients with dementia with Lewy bodies (1324 with pathological diagnosis) and 4454 controls (1216 patients with dementia with Lewy bodies vs 3791 controls in the discovery stage; 527 vs 663 in the replication stage). Results confirm previously reported associations: APOE (rs429358; odds ratio OR 2·40, 95% CI 2·14–2·70; p=1·05 × 10−48), SNCA (rs7681440; OR 0·73, 0·66–0·81; p=6·39 × 10−10), an GBA (rs35749011; OR 2·55, 1·88–3·46; p=1·78 × 10−9). They also provide some evidence for a novel candidate locus, namely CNTN1 (rs7314908; OR 1·51, 1·27–1·79; p=2·32 × 10−6); further replication will be important. Additionally, we estimate the heritable component of dementia with Lewy bodies to be about 36%.
Despite the small sample size for a genome-wide association study, and acknowledging the potential biases from ascertaining samples from multiple locations, we present the most comprehensive and well powered genetic study in dementia with Lewy bodies so far. These data show that common genetic variability has a role in the disease.
The Alzheimer's Society and the Lewy Body Society.
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