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.

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.

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.

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.

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.

Consumption of meat is associated with higher fasting glucose and insulin concentrations regardless of glucose and insulin genetic risk scores: a meta-analysis of 50,345 Caucasians.

BACKGROUND: Recent studies suggest that meat intake is associated with diabetes-related phenotypes. However, whether the associations of meat intake and glucose and insulin homeostasis are modified by genes related to glucose and insulin is unknown. OBJECTIVE: We investigated the associations of meat intake and the interaction of meat with genotype on fasting glucose and insulin concentrations in Caucasians free of diabetes mellitus. DESIGN: Fourteen studies that are part of the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium participated in the analysis. Data were provided for up to 50,345 participants. Using linear regression within studies and a fixed-effects meta-analysis across studies, we examined 1) the associations of processed meat and unprocessed red meat intake with fasting glucose and insulin concentrations; and 2) the interactions of processed meat and unprocessed red meat with genetic risk score related to fasting glucose or insulin resistance on fasting glucose and insulin concentrations. RESULTS: Processed meat was associated with higher fasting glucose, and unprocessed red meat was associated with both higher fasting glucose and fasting insulin concentrations after adjustment for potential confounders [not including body mass index (BMI)]. For every additional 50-g serving of processed meat per day, fasting glucose was 0.021 mmol/L (95% CI: 0.011, 0.030 mmol/L) higher. Every additional 100-g serving of unprocessed red meat per day was associated with a 0.037-mmol/L (95% CI: 0.023, 0.051-mmol/L) higher fasting glucose concentration and a 0.049-ln-pmol/L (95% CI: 0.035, 0.063-ln-pmol/L) higher fasting insulin concentration. After additional adjustment for BMI, observed associations were attenuated and no longer statistically significant. The association of processed meat and fasting insulin did not reach statistical significance after correction for multiple comparisons. Observed associations were not modified by genetic loci known to influence fasting glucose or insulin resistance. CONCLUSION: The association of higher fasting glucose and insulin concentrations with meat consumption was not modified by an index of glucose- and insulin-related single-nucleotide polymorphisms. Six of the participating studies are registered at clinicaltrials.gov as NCT0000513 (Atherosclerosis Risk in Communities), NCT00149435 (Cardiovascular Health Study), NCT00005136 (Family Heart Study), NCT00005121 (Framingham Heart Study), NCT00083369 (Genetics of Lipid Lowering Drugs and Diet Network), and NCT00005487 (Multi-Ethnic Study of Atherosclerosis).

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.

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.

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.

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.

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.

Large-scale meta-analysis of genome-wide association data identifies six new risk loci for Parkinson's disease.

We conducted a meta-analysis of Parkinson's disease genome-wide association studies using a common set of 7,893,274 variants across 13,708 cases and 95,282 controls. Twenty-six loci were identified as having genome-wide significant association; these and 6 additional previously reported loci were then tested in an independent set of 5,353 cases and 5,551 controls. Of the 32 tested SNPs, 24 replicated, including 6 newly identified loci. Conditional analyses within loci showed that four loci, including GBA, GAK-DGKQ, SNCA and the HLA region, contain a secondary independent risk variant. In total, we identified and replicated 28 independent risk variants for Parkinson's disease across 24 loci. Although the effect of each individual locus was small, risk profile analysis showed substantial cumulative risk in a comparison of the highest and lowest quintiles of genetic risk (odds ratio (OR) = 3.31, 95% confidence interval (CI) = 2.55-4.30; P = 2 × 10(-16)). We also show six risk loci associated with proximal gene expression or DNA methylation.

Genome-wide analysis of the heritability of amyotrophic lateral sclerosis.

IMPORTANCE: Considerable advances have been made in our understanding of the genetics underlying amyotrophic lateral sclerosis (ALS). Nevertheless, for the majority of patients who receive a diagnosis of ALS, the role played by genetics is unclear. Further elucidation of the genetic architecture of this disease will help clarify the role of genetic variation in ALS populations. OBJECTIVE: To estimate the relative importance of genetic factors in a complex disease such as ALS by accurately quantifying heritability using genome-wide data derived from genome-wide association studies. DESIGN, SETTING, AND PARTICIPANTS: We applied the genome-wide complex trait analysis algorithm to 3 genome-wide association study data sets that were generated from ALS case-control cohorts of European ancestry to estimate the heritability of ALS. Cumulatively, these data sets contained genotype data from 1223 cases and 1591 controls that had been previously generated and are publically available on the National Center for Biotechnology Information database of genotypes and phenotypes website (http://www.ncbi.nlm.nih.gov/gap). The cohorts genotyped as part of these genome-wide association study efforts include the InCHIANTI (aging in the Chianti area) Study, the Piemonte and Valle d'Aosta Register for Amyotrophic Lateral Sclerosis, the National Institute of Neurological Disorders and Stroke Repository, and an ALS specialty clinic in Helsinki, Finland. MAIN OUTCOMES AND MEASURES: A linear mixed model was used to account for all known single-nucleotide polymorphisms simultaneously and to quantify the phenotypic variance present in ostensibly outbred individuals. Variance measures were used to estimate heritability. RESULTS: With our meta-analysis, which is based on genome-wide genotyping data, we estimated the overall heritability of ALS to be approximately 21.0% (95% CI, 17.1-24.9) (SE = 2.0%), indicating that additional genetic variation influencing risk of ALS loci remains to be identified. Furthermore, we identified 17 regions of the genome that display significantly high heritability estimates. Eleven of these regions represent novel candidate regions for ALS risk. CONCLUSIONS AND RELEVANCE: We found the heritability of ALS to be significantly higher than previously reported. We also identified multiple, novel genomic regions that we hypothesize may contain causative risk variants that influence susceptibility to ALS.

Assessment of Parkinson's disease risk loci in Greece.

Genome-wide association studies (GWAS) have been shown to be a powerful approach to identify risk loci for neurodegenerative diseases. Recent GWAS in Parkinson's disease (PD) have been successful in identifying numerous risk variants pointing to novel pathways potentially implicated in the pathogenesis of PD. Contributing to these GWAS efforts, we performed genotyping of previously identified risk alleles in PD patients and control subjects from Greece. We showed that previously published risk profiles for Northern European and American populations are also applicable to the Greek population. In addition, although our study was largely underpowered to detect individual associations, we replicated 5 of 32 previously published risk variants with nominal p values <0.05. Genome-wide complex trait analysis revealed that known risk loci explain disease risk in 1.27% of Greek PD patients. Collectively, these results indicate that there is likely a substantial genetic component to PD in Greece, similarly to other worldwide populations, that remains to be discovered.

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.

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.

Analysis of genome-wide association studies of Alzheimer disease and of Parkinson disease to determine if these 2 diseases share a common genetic risk.

IMPORTANCE: Despite Alzheimer disease (AD) and Parkinson disease (PD) being clinically distinct entities, there is a possibility of a pathological overlap, with some genome-wide association (GWA) studies suggesting that the 2 diseases represent a biological continuum. The application of GWA studies to idiopathic forms of AD and PD have identified a number of loci that contain genetic variants that increase the risk of these disorders. OBJECTIVE: To assess the genetic overlap between PD and AD by testing for the presence of potentially pleiotropic loci in 2 recent GWA studies of PD and AD. DESIGN: Combined GWA analysis. SETTING: Data sets from the United Kingdom, Germany, France, and the United States. PARTICIPANTS: Thousands of patients with AD or PD and their controls. MAIN OUTCOMES AND MEASURES: Meta-analysis of GWA studies of AD and PD. METHODS: To identify evidence for potentially pleiotropic alleles that increased the risk for both PD and AD, we performed a combined PD-AD meta-analysis and compared the results with those obtained in the primary GWA studies.We also tested for a net effect of potentially polygenic alleles that were shared by both disorders by performing a polygenic score analysis. Finally, we also performed a gene-based association analysis that was aimed at detecting genes that harbor multiple disease-causing single-nucleotide polymorphisms, some of which confer a risk of PD and some a risk of AD. RESULTS: Detailed interrogation of the single-nucleotide polymorphism, polygenic, and gene-based analyses resulted in no significant evidence that supported the presence of loci that increase the risk of both PD and AD. CONCLUSIONS AND RELEVANCE: Our findings therefore imply that loci that increase the risk of both PD and AD are not widespread and that the pathological overlap could instead be "downstream" of the primary susceptibility genes that increase the risk of each disease.

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.

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.

Gene-centric meta-analysis of lipid traits in African, East Asian and Hispanic populations.

Meta-analyses of European populations has successfully identified genetic variants in over 100 loci associated with lipid levels, but our knowledge in other ethnicities remains limited. To address this, we performed dense genotyping of ∼2,000 candidate genes in 7,657 African Americans, 1,315 Hispanics and 841 East Asians, using the IBC array, a custom ∼50,000 SNP genotyping array. Meta-analyses confirmed 16 lipid loci previously established in European populations at genome-wide significance level, and found multiple independent association signals within these lipid loci. Initial discovery and in silico follow-up in 7,000 additional African American samples, confirmed two novel loci: rs5030359 within ICAM1 is associated with total cholesterol (TC) and low-density lipoprotein cholesterol (LDL-C) (p = 8.8×10(-7) and p = 1.5×10(-6) respectively) and a nonsense mutation rs3211938 within CD36 is associated with high-density lipoprotein cholesterol (HDL-C) levels (p = 13.5×10(-12)). The rs3211938-G allele, which is nearly absent in European and Asian populations, has been previously found to be associated with CD36 deficiency and shows a signature of selection in Africans and African Americans. Finally, we have evaluated the effect of SNPs established in European populations on lipid levels in multi-ethnic populations and show that most known lipid association signals span across ethnicities. However, differences between populations, especially differences in allele frequency, can be leveraged to identify novel signals, as shown by the discovery of ICAM1 and CD36 in the current report.