Citations

Abstract Background Epidemiological studies that examined the association between Parkinson's disease (PD) and cancers led to inconsistent results, but they face a number of methodological difficulties. Objective We used results from genome‐wide association studies (GWASs) to study the genetic correlation between PD and different cancers to identify common genetic risk factors. Methods We used individual data for participants of European ancestry from the Courage‐PD (Comprehensive Unbiased Risk Factor Assessment for Genetics and Environment in Parkinson's Disease; PD, N = 16,519) and EPITHYR (differentiated thyroid cancer, N = 3527) consortia and summary statistics of GWASs from iPDGC (International Parkinson Disease Genomics Consortium; PD, N = 482,730), Melanoma Meta‐Analysis Consortium (MMAC), Breast Cancer Association Consortium (breast cancer), the Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome (prostate cancer), International Lung Cancer Consortium (lung cancer), and Ovarian Cancer Association Consortium (ovarian cancer) (N comprised between 36,017 and 228,951 for cancer GWASs). We estimated the genetic correlation between PD and cancers using linkage disequilibrium score regression. We studied the association between PD and polymorphisms associated with cancers, and vice versa, using cross‐phenotypes polygenic risk score (PRS) analyses. Results We confirmed a previously reported positive genetic correlation of PD with melanoma (G corr = 0.16 [0.04; 0.28]) and reported an additional significant positive correlation of PD with prostate cancer (G corr = 0.11 [0.03; 0.19]). There was a significant inverse association between the PRS for ovarian cancer and PD (odds ratio [OR] = 0.89 [0.84; 0.94]). Conversely, the PRS of PD was positively associated with breast cancer (OR = 1.08 [1.06; 1.10]) and inversely associated with ovarian cancer (OR = 0.95 [0.91; 0.99]). The association between PD and ovarian cancer was mostly driven by rs183211 located in an intron of the NSF gene (17q21.31). Conclusions We show evidence in favor of a contribution of pleiotropic genes to the association between PD and specific cancers. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

Abstract Background Mendelian randomization (MR) studies are susceptible to metadata errors (e.g. incorrect specification of the effect allele column) and other analytical issues that can introduce substantial bias into analyses. We developed a quality control (QC) pipeline for the Fatty Acids in Cancer Mendelian Randomization Collaboration (FAMRC) that can be used to identify and correct for such errors. Methods We collated summary association statistics from fatty acid and cancer genome-wide association studies (GWAS) and subjected the collated data to a comprehensive QC pipeline. We identified metadata errors through comparison of study-specific statistics to external reference data sets (the National Human Genome Research Institute-European Bioinformatics Institute GWAS catalogue and 1000 genome super populations) and other analytical issues through comparison of reported to expected genetic effect sizes. Comparisons were based on three sets of genetic variants: (i) GWAS hits for fatty acids, (ii) GWAS hits for cancer and (iii) a 1000 genomes reference set. Results We collated summary data from 6 fatty acid and 54 cancer GWAS. Metadata errors and analytical issues with the potential to introduce substantial bias were identified in seven studies (11.6%). After resolving metadata errors and analytical issues, we created a data set of 219 842 genetic associations with 90 cancer types, generated in analyses of 566 665 cancer cases and 1 622 374 controls. Conclusions In this large MR collaboration, 11.6% of included studies were affected by a substantial metadata error or analytical issue. By increasing the integrity of collated summary data prior to their analysis, our protocol can be used to increase the reliability of downstream MR analyses. Our pipeline is available to other researchers via the CheckSumStats package (https://github.com/MRCIEU/CheckSumStats).

Background Methods: The question prompt list content was derived through a modified Delphi process consisting of 3 rounds. In round 1, experts provided 5 answers to the prompts “What general questions should patients ask when given a new diagnosis of Barrett’s esophagus” and “What questions do I not hear patients asking, but given my expertise, I believe they should be asking?” Questions were reviewed and categorized into themes. In round 2, experts rated questions on a 5-point Likert scale. In round 3, experts rerated questions modified or reduced after the previous rounds. Only questions rated as “essential” or “important” were included in Barrett’s esophagus question prompt list (BE-QPL). To improve usability, questions were reduced to minimize redundancy and simplified to use language at an eighth-grade level (Fig. 1). Results: Twenty-one esophageal medical and surgical experts participated in both rounds (91% males; median age 52 years). The expert panel comprised of 33% esophagologists, 24% foregut surgeons, and 24% advanced endoscopists, with a median of 15 years in clinical practice. Most (81%), worked in an academic tertiary referral hospital. In this 3-round Delphi technique, 220 questions were proposed in round 1, 122 (55.5%) were accepted into the BE-QPL and reduced down to 76 questions (round 2), and 67 questions (round 3). These 67 questions reached a Flesch Reading Ease of 68.8, interpreted as easily understood by 13 to 15 years olds. Conclusions: With multidisciplinary input, we have developed a physician-derived BE-QPL to optimize patient-physician communication. Future directions will seek patient feedback to distill the questions further to a smaller number and then assess their usability.

SummaryLeukaemic stem cell (LSC) gene expression has recently been linked to prognosis in patients with acute myeloid leukaemia (17‐gene LSC score, LSC‐17) and myelodysplastic syndromes. Although chronic myelomonocytic leukaemia (CMML) is regarded as a stem cell disorder, the clinical and biological impact of LSCs on CMML patients remains elusive. Making use of multiple independent validation cohorts, we here describe a concise three‐gene expression signature (LSC‐3, derived from the LSC‐17 score) as an independent and robust prognostic factor for leukaemia‐free and overall survival in CMML. We propose that LSC‐3 could be used to supplement existing risk stratification systems, to improve prognostic performance and guide management decisions.

AbstractBackgroundIn familial frontotemporal lobar degeneration (f‐FTLD), plasma levels of neurofilament light (NfL) are elevated at least two years prior to symptom onset and predict future clinical status. The Neurofilament Surveillance Project (NSP), an actively recruiting observational study, seeks to obtain higher resolution data of temporal changes in plasma NfL to better understand its clinical utility in f‐FTLD interventional trials. The NSP is a pre‐competitive collaboration sponsored by the Bluefield Project to Cure FTD and funded by biotechnology and pharmaceutical companies and nonprofit organizations.MethodParticipants must be members of families with disease‐causing mutations in C9orf72, MAPT or GRN and enrolled in the ALLFTD natural history study. Up to 335 participants, with roughly equal representation across mutation type, provide plasma quarterly for 3 years (4355 samples total) to enable the observation of peripheral NfL levels longitudinally during disease onset and progression. Plasma is collected by certified mobile research nurses during remote visits, and NfL is measured in batch at least every 6 months. NfL measurements from one plasma aliquot per draw will be correlated with annual assessments obtained in the ALLFTD study, including measures of disease severity (CDRÒ+NACC‐FTLD, CGI, etc.), cognitive function from the UDS Neuropsychology Battery, and volumetric MRI data. Additional plasma aliquots are reserved for future analyses of other biomarkers during the course of the study; another subset of aliquots is reserved to share with interested investigators after the study ends.ResultAs of 1/19/22, the NSP had enrolled 161 participants, including 62 from C9orf72 kindreds, 60 from MAPT kindreds, and 28 from GRN kindreds. One‐hundred forty‐five participants had completed their initial visit, and 109 had completed more than 3, and up to 5, quarterly blood draws. Enrollment and study visits are ongoing despite COVID‐related limitations.ConclusionThe quarterly blood sampling from this study, combined with annual comprehensive clinical assessments through the ALLFTD natural history study, will enable a more detailed understanding of when and how NfL levels change during phenoconversion and/or disease progression in f‐FTLD mutation carriers. These data will be especially informative in the context of the targeted investigational therapeutics for f‐FTLD now entering clinical trials.

Previously we showed the generation of a protein trap library made with the gene-break transposon (GBT) in zebrafish ( Danio rerio ) that could be used to facilitate novel functional genome annotation towards understanding molecular underpinnings of human diseases (Ichino et al, 2020). Here, we report a significant application of this library for discovering essential genes for heart rhythm disorders such as sick sinus syndrome (SSS). SSS is a group of heart rhythm disorders caused by malfunction of the sinus node, the heart’s primary pacemaker. Partially owing to its aging-associated phenotypic manifestation and low expressivity, molecular mechanisms of SSS remain difficult to decipher. From 609 GBT lines screened, we generated a collection of 35 zebrafish insertional cardiac (ZIC) mutants in which each mutant traps a gene with cardiac expression. We further employed electrocardiographic measurements to screen these 35 ZIC lines and identified three GBT mutants with SSS-like phenotypes. More detailed functional studies on one of the arrhythmogenic mutants, GBT411 , in both zebrafish and mouse models unveiled Dnajb6 as a novel SSS causative gene with a unique expression pattern within the subpopulation of sinus node pacemaker cells that partially overlaps with the expression of hyperpolarization activated cyclic nucleotide gated channel 4 (HCN4), supporting heterogeneity of the cardiac pacemaker cells.

AbstractBackgroundKnown risk alleles for epithelial ovarian cancer (EOC) account for approximately 40% of the heritability for EOC. Copy number variants (CNVs) have not been investigated as EOC risk alleles in a large population cohort.MethodsSingle nucleotide polymorphism array data from 13 071 EOC cases and 17 306 controls of White European ancestry were used to identify CNVs associated with EOC risk using a rare admixture maximum likelihood test for gene burden and a by-probe ratio test. We performed enrichment analysis of CNVs at known EOC risk loci and functional biofeatures in ovarian cancer–related cell types.ResultsWe identified statistically significant risk associations with CNVs at known EOC risk genes; BRCA1 (PEOC = 1.60E-21; OREOC = 8.24), RAD51C (Phigh-grade serous ovarian cancer [HGSOC] = 5.5E-4; odds ratio [OR]HGSOC = 5.74 del), and BRCA2 (PHGSOC = 7.0E-4; ORHGSOC = 3.31 deletion). Four suggestive associations (P < .001) were identified for rare CNVs. Risk-associated CNVs were enriched (P < .05) at known EOC risk loci identified by genome-wide association study. Noncoding CNVs were enriched in active promoters and insulators in EOC-related cell types.ConclusionsCNVs in BRCA1 have been previously reported in smaller studies, but their observed frequency in this large population-based cohort, along with the CNVs observed at BRCA2 and RAD51C gene loci in EOC cases, suggests that these CNVs are potentially pathogenic and may contribute to the spectrum of disease-causing mutations in these genes. CNVs are likely to occur in a wider set of susceptibility regions, with potential implications for clinical genetic testing and disease prevention.