Genome-wide Trans-ethnic Meta-analysis Identifies Seven Genetic Loci Influencing Erythrocyte Traits and a Role for RBPMS in Erythropoiesis.

Genome-wide association studies (GWASs) have identified loci for erythrocyte traits in primarily European ancestry populations. We conducted GWAS meta-analyses of six erythrocyte traits in 71,638 individuals from European, East Asian, and African ancestries using a Bayesian approach to account for heterogeneity in allelic effects and variation in the structure of linkage disequilibrium between ethnicities. We identified seven loci for erythrocyte traits including a locus (RBPMS/GTF2E2) associated with mean corpuscular hemoglobin and mean corpuscular volume. Statistical fine-mapping at this locus pointed to RBPMS at this locus and excluded nearby GTF2E2. Using zebrafish morpholino to evaluate loss of function, we observed a strong in vivo erythropoietic effect for RBPMS but not for GTF2E2, supporting the statistical fine-mapping at this locus and demonstrating that RBPMS is a regulator of erythropoiesis. Our findings show the utility of trans-ethnic GWASs for discovery and characterization of genetic loci influencing hematologic traits.

Detection of genetic loci associated with plasma fetuin-A: a meta-analysis of genome-wide association studies from the CHARGE Consortium.

Plasma fetuin-A is associated with type 2 diabetes, and AHSG, the gene encoding fetuin-A, has been identified as a susceptibility locus for diabetes and metabolic syndrome. Thus far, unbiased investigations of the genetic determinants of plasma fetuin-A concentrations have not been conducted. We searched for single nucleotide polymorphisms (SNPs) related to fetuin-A concentrations by a genome-wide association study in six population-based studies. We examined the association of fetuin-A levels with ∼ 2.5 million genotyped and imputed SNPs in 9,055 participants of European descent and 2,119 African Americans. In both ethnicities, the strongest associations were centered in a region with a high degree of LD near the AHSG locus. Among 136 genome-wide significant (P < 0.05 × 10-8) SNPs near the AHSG locus, the top SNP was rs4917 (P =1.27 × 10-303), a known coding SNP in exon 6 that is associated with a 0.06 g/l (∼13%) lower fetuin-A level. This variant alone explained 14% of the variation in fetuin-A levels. Analyses conditioned on rs4917 indicated that the strong association with the AHSG locus stems from additional independent associations of multiple variants among European Americans. In conclusion, levels of fetuin-A in plasma are strongly associated with SNPs in its encoding gene, AHSG, but not elsewhere in the genome. Given the strength of the associations observed for multiple independent SNPs, the AHSG gene is an example of a candidate locus suitable for additional investigations including fine mapping to elucidate the biological basis of the findings and further functional experiments to clarify AHSG as a potential therapeutic target.

Genetic comorbidities in Parkinson's disease.

Parkinson's disease (PD) has a number of known genetic risk factors. Clinical and epidemiological studies have suggested the existence of intermediate factors that may be associated with additional risk of PD. We construct genetic risk profiles for additional epidemiological and clinical factors using known genome-wide association studies (GWAS) loci related to these specific phenotypes to estimate genetic comorbidity in a systematic review. We identify genetic risk profiles based on GWAS variants associated with schizophrenia and Crohn's disease as significantly associated with risk of PD. Conditional analyses adjusting for SNPs near loci associated with PD and schizophrenia or PD and Crohn's disease suggest that spatially overlapping loci associated with schizophrenia and PD account for most of the shared comorbidity, while variation outside of known proximal loci shared by PD and Crohn's disease accounts for their shared genetic comorbidity. We examine brain methylation and expression signatures proximal to schizophrenia and Crohn's disease loci to infer functional changes in the brain associated with the variants contributing to genetic comorbidity. We compare our results with a systematic review of epidemiological literature, while the findings are dissimilar to a degree; marginal genetic associations corroborate the directionality of associations across genetic and epidemiological data. We show a strong genetically defined level of comorbidity between PD and Crohn's disease as well as between PD and schizophrenia, with likely functional consequences of associated variants occurring in brain.

Trans-ethnic meta-analysis of white blood cell phenotypes.

White blood cell (WBC) count is a common clinical measure used as a predictor of certain aspects of human health, including immunity and infection status. WBC count is also a complex trait that varies among individuals and ancestry groups. Differences in linkage disequilibrium structure and heterogeneity in allelic effects are expected to play a role in the associations observed between populations. Prior genome-wide association study (GWAS) meta-analyses have identified genomic loci associated with WBC and its subtypes, but much of the heritability of these phenotypes remains unexplained. Using GWAS summary statistics for over 50 000 individuals from three diverse populations (Japanese, African-American and European ancestry), a Bayesian model methodology was employed to account for heterogeneity between ancestry groups. This approach was used to perform a trans-ethnic meta-analysis of total WBC, neutrophil and monocyte counts. Ten previously known associations were replicated and six new loci were identified, including several regions harboring genes related to inflammation and immune cell function. Ninety-five percent credible interval regions were calculated to narrow the association signals and fine-map the putatively causal variants within loci. Finally, a conditional analysis was performed on the most significant SNPs identified by the trans-ethnic meta-analysis (MA), and nine secondary signals within loci previously associated with WBC or its subtypes were identified. This work illustrates the potential of trans-ethnic analysis and ascribes a critical role to multi-ethnic cohorts and consortia in exploring complex phenotypes with respect to variants that lie outside the European-biased GWAS pool.

Genome-wide association analysis of blood-pressure traits in African-ancestry individuals reveals common associated genes in African and non-African populations.

High blood pressure (BP) is more prevalent and contributes to more severe manifestations of cardiovascular disease (CVD) in African Americans than in any other United States ethnic group. Several small African-ancestry (AA) BP genome-wide association studies (GWASs) have been published, but their findings have failed to replicate to date. We report on a large AA BP GWAS meta-analysis that includes 29,378 individuals from 19 discovery cohorts and subsequent replication in additional samples of AA (n = 10,386), European ancestry (EA) (n = 69,395), and East Asian ancestry (n = 19,601). Five loci (EVX1-HOXA, ULK4, RSPO3, PLEKHG1, and SOX6) reached genome-wide significance (p < 1.0 × 10(-8)) for either systolic or diastolic BP in a transethnic meta-analysis after correction for multiple testing. Three of these BP loci (EVX1-HOXA, RSPO3, and PLEKHG1) lack previous associations with BP. We also identified one independent signal in a known BP locus (SOX6) and provide evidence for fine mapping in four additional validated BP loci. We also demonstrate that validated EA BP GWAS loci, considered jointly, show significant effects in AA samples. Consequently, these findings suggest that BP loci might have universal effects across studied populations, demonstrating that multiethnic samples are an essential component in identifying, fine mapping, and understanding their trait variability.

Gain-of-function lipoprotein lipase variant rs13702 modulates lipid traits through disruption of a microRNA-410 seed site.

Genome-wide association studies (GWAS) have identified hundreds of genetic variants that are associated with lipid phenotypes. However, data supporting a functional role for these variants in the context of lipid metabolism are scarce. We investigated the association of the lipoprotein lipase (LPL) variant rs13702 with plasma lipids and explored its potential for functionality. The rs13702 minor allele had been predicted to disrupt a microRNA (miR) recognition element (MRE) seed site (MRESS) for the human microRNA-410 (miR-410). Furthermore, rs13702 is in linkage disequilibrium (LD) with several SNPs identified by GWAS. We performed a meta-analysis across ten cohorts of participants that showed a statistically significant association of rs13702 with triacylglycerols (TAG) (p = 3.18 × 10(-42)) and high-density lipoprotein cholesterol (HDL-C) (p = 1.35 × 10(-32)) with each copy of the minor allele associated with 0.060 mmol/l lower TAG and 0.041 mmol/l higher HDL-C. Our data showed that an LPL 3' UTR luciferase reporter carrying the rs13702 major T allele was reduced by 40% in response to a miR-410 mimic. We also evaluated the interaction between intake of dietary fatty acids and rs13702. Meta-analysis demonstrated a significant interaction between rs13702 and dietary polyunsaturated fatty acid (PUFA) with respect to TAG concentrations (p = 0.00153), with the magnitude of the inverse association between dietary PUFA intake and TAG concentration showing -0.007 mmol/l greater reduction. Our results suggest that rs13702 induces the allele-specific regulation of LPL by miR-410 in humans. This work provides biological and potential clinical relevance for previously reported GWAS variants associated with plasma lipid phenotypes.

Baseline genetic associations in the Parkinson's Progression Markers Initiative (PPMI).

BACKGROUND: The Parkinson's Progression Marker Initiative is an international multicenter study whose main goal is investigating markers for Parkinson's disease (PD) progression as part of a path to a treatment for the disease. This manuscript describes the baseline genetic architecture of this study, providing not only a catalog of disease-linked variants and mutations, but also quantitative measures with which to adjust for population structure. METHODS: Three hundred eighty-three newly diagnosed typical PD cases, 65 atypical PD and 178 healthy controls, from the Parkinson's Progression Marker Initiative study have been genotyped on the NeuroX or Immunochip arrays. These data are freely available to all researchers interested in pursuing PD research within the Parkinson's Progression Marker Initiative. RESULTS: The Parkinson's Progression Marker Initiative represents a study population with low genetic heterogeneity. We recapitulate known PD associations from large-scale genome-wide association studies and refine genetic risk score models for PD predictability (area under the curve, ∼0.74). We show the presence of six LRRK2 p.G2019S and nine GBA p.N370S mutation carriers. CONCLUSIONS: The Parkinson's Progression Marker Initiative study and its genetic data are useful in studies of PD biomarkers. The genetic architecture described here will be useful in the analysis of myriad biological and clinical traits within this study.

Genome-wide association analysis of red blood cell traits in African Americans: the COGENT Network.

Laboratory red blood cell (RBC) measurements are clinically important, heritable and differ among ethnic groups. To identify genetic variants that contribute to RBC phenotypes in African Americans (AAs), we conducted a genome-wide association study in up to ~16 500 AAs. The alpha-globin locus on chromosome 16pter [lead SNP rs13335629 in ITFG3 gene; P < 1E-13 for hemoglobin (Hgb), RBC count, mean corpuscular volume (MCV), MCH and MCHC] and the G6PD locus on Xq28 [lead SNP rs1050828; P < 1E - 13 for Hgb, hematocrit (Hct), MCV, RBC count and red cell distribution width (RDW)] were each associated with multiple RBC traits. At the alpha-globin region, both the common African 3.7 kb deletion and common single nucleotide polymorphisms (SNPs) appear to contribute independently to RBC phenotypes among AAs. In the 2p21 region, we identified a novel variant of PRKCE distinctly associated with Hct in AAs. In a genome-wide admixture mapping scan, local European ancestry at the 6p22 region containing HFE and LRRC16A was associated with higher Hgb. LRRC16A has been previously associated with the platelet count and mean platelet volume in AAs, but not with Hgb. Finally, we extended to AAs the findings of association of erythrocyte traits with several loci previously reported in Europeans and/or Asians, including CD164 and HBS1L-MYB. In summary, this large-scale genome-wide analysis in AAs has extended the importance of several RBC-associated genetic loci to AAs and identified allelic heterogeneity and pleiotropy at several previously known genetic loci associated with blood cell traits in AAs.

Genetic risk and age in Parkinson's disease: Continuum not stratum.

BACKGROUND: Recent genomewide association study meta-analyses have identified 28 loci associated with risk of Parkinson's disease (PD). We sought to investigate whether these genetic risk factors are associated with PD age at onset. METHODS: Genetic risk scores from these loci were calculated for 6,249 cases. Linear regression tested associations between cumulative genetic risk and PD age at onset. RESULTS: Increasing genetic risk scores were associated with earlier age at onset (beta = -0.10, P = 2.92 × 10(-8) , adjusted r(2) = 0.27). Single standard deviation increase in genetic risk score is associated with 37.44 d earlier age at onset. Highest genetic risk was found at 31 to 60 y, onset slightly below average age at onset (AAO). CONCLUSIONS: Common genetic risk factors have a small but consistent association with AAO in PD.

Using genome-wide complex trait analysis to quantify 'missing heritability' in Parkinson's disease.

Genome-wide association studies (GWASs) have been successful at identifying single-nucleotide polymorphisms (SNPs) highly associated with common traits; however, a great deal of the heritable variation associated with common traits remains unaccounted for within the genome. Genome-wide complex trait analysis (GCTA) is a statistical method that applies a linear mixed model to estimate phenotypic variance of complex traits explained by genome-wide SNPs, including those not associated with the trait in a GWAS. We applied GCTA to 8 cohorts containing 7096 case and 19 455 control individuals of European ancestry in order to examine the missing heritability present in Parkinson's disease (PD). We meta-analyzed our initial results to produce robust heritability estimates for PD types across cohorts. Our results identify 27% (95% CI 17-38, P = 8.08E - 08) phenotypic variance associated with all types of PD, 15% (95% CI -0.2 to 33, P = 0.09) phenotypic variance associated with early-onset PD and 31% (95% CI 17-44, P = 1.34E - 05) phenotypic variance associated with late-onset PD. This is a substantial increase from the genetic variance identified by top GWAS hits alone (between 3 and 5%) and indicates there are substantially more risk loci to be identified. Our results suggest that although GWASs are a useful tool in identifying the most common variants associated with complex disease, a great deal of common variants of small effect remain to be discovered.

Serum iron levels and the risk of Parkinson disease: a Mendelian randomization study.

BACKGROUND: Although levels of iron are known to be increased in the brains of patients with Parkinson disease (PD), epidemiological evidence on a possible effect of iron blood levels on PD risk is inconclusive, with effects reported in opposite directions. Epidemiological studies suffer from problems of confounding and reverse causation, and mendelian randomization (MR) represents an alternative approach to provide unconfounded estimates of the effects of biomarkers on disease. We performed a MR study where genes known to modify iron levels were used as instruments to estimate the effect of iron on PD risk, based on estimates of the genetic effects on both iron and PD obtained from the largest sample meta-analyzed to date. METHODS AND FINDINGS: We used as instrumental variables three genetic variants influencing iron levels, HFE rs1800562, HFE rs1799945, and TMPRSS6 rs855791. Estimates of their effect on serum iron were based on a recent genome-wide meta-analysis of 21,567 individuals, while estimates of their effect on PD risk were obtained through meta-analysis of genome-wide and candidate gene studies with 20,809 PD cases and 88,892 controls. Separate MR estimates of the effect of iron on PD were obtained for each variant and pooled by meta-analysis. We investigated heterogeneity across the three estimates as an indication of possible pleiotropy and found no evidence of it. The combined MR estimate showed a statistically significant protective effect of iron, with a relative risk reduction for PD of 3% (95% CI 1%-6%; p = 0.001) per 10 µg/dl increase in serum iron. CONCLUSIONS: Our study suggests that increased iron levels are causally associated with a decreased risk of developing PD. Further studies are needed to understand the pathophysiological mechanism of action of serum iron on PD risk before recommendations can be made.

Women in Combat Need a Collaborative Culture Shift.

The 2021 Women in Combat (WIC) Symposium brought together hundreds of service members, researchers, and multidisciplinary leaders for 3 days of virtual education and interactive discussion regarding female leadership, operational performance, and physical health and well-being. Three days of presentations were followed by virtual face-to-face breakout room sessions that aimed to identify gaps currently impacting military servicewomen, mirroring the inaugural WIC Symposium held in 2014. Keynote speakers revisited old recommendations and redefined these in the context of new research and policy changes within the Department of Defense (DoD), making it apparent that although much work has been done, policy and practice are yet to fully integrate the research recommendations that will improve the health and wellness of servicewomen. Originally planned as an in-person meeting, the WIC Symposium was held completely online because of the sustained threat of the COVID-19 pandemic. This event was collectively attended by nearly 10,000 people, reflecting an attendance of over ten times the number of registered attendees. The 2021 WIC Symposium was successful in part because of the groundwork laid by previous researchers who laid out virtual meeting best practices and in part because of the increased accessibility of an online event.

Leaders, Talent Management, and Allies: The Keys to Successful Integration in the Combat Arms.

Servicewomen enhance the U.S. Military fighting force by bringing diverse perspectives, collaborative and creative problem-solving skills for global peace and security, and innovative, adaptive talent as leaders. Despite servicewomen integrating into combat units over the past decade, a number of barriers remain related to inclusion, promotion, and quality of life, particularly for marginalized women. To eliminate inequities experienced by servicewomen, leaders across all levels of the military play a key role in supporting the successful integration of servicewomen, cultivating an environment of belonging, and guarding against toxicity, which will result in optimized performance and readiness for all servicemembers in defense of the Nation. Herein, we review the original gaps related to leadership and peer behaviors identified by the 2014 Women in Combat Symposium, provide updates in the literature, address the topics that arose at the 2021 Women in Combat Symposium, and finally, outline the remaining barriers and challenges to the successful integration of female servicemembers.

Physical Health and Well-being: Updates and the Way Ahead.

INTRODUCTION: The Women in Combat Summit 2021 "Forging the Future: How Women Enhance the Fighting Force" took place during February 9-11, 2021, via a virtual conference platform. The third and final day of the Summit regarded the physical health and well-being of military women and included the topics of urogenital health, nutrition and iron-deficiency anemia, unintended pregnancy and contraception, and traumatic brain injury. MATERIALS AND METHODS: After presentations on the topics earlier, interested conference attendees were invited to participate in focus groups to discuss and review policy recommendations for physical health and well-being in military women. Discussions centered around the topics discussed during the presentations, and suggestions for future Women in Combat Summits were noted. Specifics of the methods of the Summit are presented elsewhere in this supplement. RESULTS: We formulated research and policy recommendations for urogenital health, nutrition and iron-deficiency anemia, contraception and unintended pregnancy, and traumatic brain injury. CONCLUSIONS: In order to continue to develop the future health of military women, health care providers, researchers, and policymakers should consider the recommendations made in this supplement as they continue to build on the state of the science and forge the future.

Physiology of Health and Performance: Enabling Success of Women in Combat Arms Roles.

INTRODUCTION: The modern female soldier has yet to be fully characterized as she steps up to fill new combat roles that have only recently been opened to women. Both U.S. and U.K. military operational research efforts are supporting a science-based evolution of physical training and standards for female warfighters. The increasing representation of women in all military occupations makes it possible to discover and document the limits of female physiological performance. METHOD: An informal Delphi process was used to synthesize an integrated concept of current military female physiological research priorities and emerging findings using a panel of subject matter experts who presented their research and perspectives during the second Women in Combat Summit hosted by the TriService Nursing Research Program in February 2021. RESULTS: The physical characteristics of the modern soldier are changing as women train for nontraditional military roles, and they are emerging as stronger and leaner. Capabilities and physique will likely continue to evolve in response to new Army standards and training programs designed around science-based sex-neutral requirements. Strong bones may be a feature of the female pioneers who successfully complete training and secure roles traditionally reserved for men. Injury risk can be reduced by smarter, targeted training and with attention directed to female-specific hormonal status, biomechanics, and musculoskeletal architecture. An "estrogen advantage" appears to metabolically support enhanced mental endurance in physically demanding high-stress field conditions; a healthy estrogen environment is also essential for musculoskeletal health. The performance of female soldiers can be further enhanced by attention to equipment that serves their needs with seemingly simple solutions such as a suitable sports bra and personal protective equipment that accommodates the female anatomy. CONCLUSIONS: Female physiological limits and performance have yet to be adequately defined as women move into new roles that were previously developed and reserved for men. Emerging evidence indicates much greater physical capacity and physiological resilience than previously postulated.

Use of support vector machines for disease risk prediction in genome-wide association studies: concerns and opportunities.

The success of genome-wide association studies (GWAS) in deciphering the genetic architecture of complex diseases has fueled the expectations whether the individual risk can also be quantified based on the genetic architecture. So far, disease risk prediction based on top-validated single-nucleotide polymorphisms (SNPs) showed little predictive value. Here, we applied a support vector machine (SVM) to Parkinson disease (PD) and type 1 diabetes (T1D), to show that apart from magnitude of effect size of risk variants, heritability of the disease also plays an important role in disease risk prediction. Furthermore, we performed a simulation study to show the role of uncommon (frequency 1-5%) as well as rare variants (frequency <1%) in disease etiology of complex diseases. Using a cross-validation model, we were able to achieve predictions with an area under the receiver operating characteristic curve (AUC) of ~0.88 for T1D, highlighting the strong heritable component (∼90%). This is in contrast to PD, where we were unable to achieve a satisfactory prediction (AUC ~0.56; heritability ~38%). Our simulations showed that simultaneous inclusion of uncommon and rare variants in GWAS would eventually lead to feasible disease risk prediction for complex diseases such as PD. The used software is available at http://www.ra.cs.uni-tuebingen.de/software/MACLEAPS/.

Preventing Postoperative Nausea and Vomiting During an Ondansetron Shortage.

Postoperative nausea and vomiting (PONV) degrades patient experience and increases healthcare costs. Estimates of PONV range from 10% to 80%. The Apfel Simplified Score is an evidence-based instrument for determining individual risk of PONV. Scoring enables anesthesia providers to match antiemetic strategies with the calculated risk of PONV. Data were collected across 3 times. After the Apfel scoring system was automated into the electronic medical record, providers were more likely to increase PONV prophylaxis for patients at highest risk and reduce prophylaxis for patients at lowest risk. Rates of PONV remained similar at baseline (34.7%) and in the early postimplementation period (38.8%); a modest reduction was observed in the final period (26.5%). Intravenous ondansetron, the most common antiemetic at baseline, was not available in the early postimplementation period, which may partially explain the initial increase in PONV. While ondansetron was unavailable, providers began using 3 other antiemetics, a practice that persisted once intravenous ondansetron returned. The Apfel score is an evidence-based tool that providers can use to reduce the risk of PONV. This electronic tool and the reminder cards have been shared across the US Military Health System, fostering an organizational culture that values targeted prophylaxis for PONV.

NeuroX, a fast and efficient genotyping platform for investigation of neurodegenerative diseases.

Our objective was to design a genotyping platform that would allow rapid genetic characterization of samples in the context of genetic mutations and risk factors associated with common neurodegenerative diseases. The platform needed to be relatively affordable, rapid to deploy, and use a common and accessible technology. Central to this project, we wanted to make the content of the platform open to any investigator without restriction. In designing this array we prioritized a number of types of genetic variability for inclusion, such as known risk alleles, disease-causing mutations, putative risk alleles, and other functionally important variants. The array was primarily designed to allow rapid screening of samples for disease-causing mutations and large population studies of risk factors. Notably, an explicit aim was to make this array widely available to facilitate data sharing across and within diseases. The resulting array, NeuroX, is a remarkably cost and time effective solution for high-quality genotyping. NeuroX comprises a backbone of standard Illumina exome content of approximately 240,000 variants, and over 24,000 custom content variants focusing on neurologic diseases. Data are generated at approximately $50-$60 per sample using a 12-sample format chip and regular Infinium infrastructure; thus, genotyping is rapid and accessible to many investigators. Here, we describe the design of NeuroX, discuss the utility of NeuroX in the analyses of rare and common risk variants, and present quality control metrics and a brief primer for the analysis of NeuroX derived data.

Diagnosis of Parkinson's disease on the basis of clinical and genetic classification: a population-based modelling study.

BACKGROUND: Accurate diagnosis and early detection of complex diseases, such as Parkinson's disease, has the potential to be of great benefit for researchers and clinical practice. We aimed to create a non-invasive, accurate classification model for the diagnosis of Parkinson's disease, which could serve as a basis for future disease prediction studies in longitudinal cohorts. METHODS: We developed a model for disease classification using data from the Parkinson's Progression Marker Initiative (PPMI) study for 367 patients with Parkinson's disease and phenotypically typical imaging data and 165 controls without neurological disease. Olfactory function, genetic risk, family history of Parkinson's disease, age, and gender were algorithmically selected by stepwise logistic regression as significant contributors to our classifying model. We then tested the model with data from 825 patients with Parkinson's disease and 261 controls from five independent cohorts with varying recruitment strategies and designs: the Parkinson's Disease Biomarkers Program (PDBP), the Parkinson's Associated Risk Study (PARS), 23andMe, the Longitudinal and Biomarker Study in PD (LABS-PD), and the Morris K Udall Parkinson's Disease Research Center of Excellence cohort (Penn-Udall). Additionally, we used our model to investigate patients who had imaging scans without evidence of dopaminergic deficit (SWEDD). FINDINGS: In the population from PPMI, our initial model correctly distinguished patients with Parkinson's disease from controls at an area under the curve (AUC) of 0·923 (95% CI 0·900-0·946) with high sensitivity (0·834, 95% CI 0·711-0·883) and specificity (0·903, 95% CI 0·824-0·946) at its optimum AUC threshold (0·655). All Hosmer-Lemeshow simulations suggested that when parsed into random subgroups, the subgroup data matched that of the overall cohort. External validation showed good classification of Parkinson's disease, with AUCs of 0·894 (95% CI 0·867-0·921) in the PDBP cohort, 0·998 (0·992-1·000) in PARS, 0·955 (no 95% CI available) in 23andMe, 0·929 (0·896-0·962) in LABS-PD, and 0·939 (0·891-0·986) in the Penn-Udall cohort. Four of 17 SWEDD participants who our model classified as having Parkinson's disease converted to Parkinson's disease within 1 year, whereas only one of 38 SWEDD participants who were not classified as having Parkinson's disease underwent conversion (test of proportions, p=0·003). INTERPRETATION: Our model provides a potential new approach to distinguish participants with Parkinson's disease from controls. If the model can also identify individuals with prodromal or preclinical Parkinson's disease in prospective cohorts, it could facilitate identification of biomarkers and interventions. FUNDING: National Institute on Aging, National Institute of Neurological Disorders and Stroke, and the Michael J Fox Foundation.

Large-scale genomic analyses link reproductive aging to hypothalamic signaling, breast cancer susceptibility and BRCA1-mediated DNA repair.

Menopause timing has a substantial impact on infertility and risk of disease, including breast cancer, but the underlying mechanisms are poorly understood. We report a dual strategy in ∼70,000 women to identify common and low-frequency protein-coding variation associated with age at natural menopause (ANM). We identified 44 regions with common variants, including two regions harboring additional rare missense alleles of large effect. We found enrichment of signals in or near genes involved in delayed puberty, highlighting the first molecular links between the onset and end of reproductive lifespan. Pathway analyses identified major association with DNA damage response (DDR) genes, including the first common coding variant in BRCA1 associated with any complex trait. Mendelian randomization analyses supported a causal effect of later ANM on breast cancer risk (∼6% increase in risk per year; P = 3 × 10(-14)), likely mediated by prolonged sex hormone exposure rather than DDR mechanisms.