Common DNA variants predict tall stature in Europeans

Genome-Wide Genetic Associations Prioritize Evaluation of Causal Mechanisms of Atherosclerotic Disease Risk

OBJECTIVE

The goal of this review is to discuss the implementation of genome-wide association studies to identify causal mechanisms of vascular disease risk.

APPROACH AND RESULTS

The history of genome-wide association studies is described, the use of imputation and the creation of consortia to conduct meta-analyses with sufficient power to arrive at consistent associated loci for vascular disease. Genomic methods are described that allow the identification of causal variants and causal genes and how they impact the disease process. The power of single-cell analyses to promote genome-wide association studies of causal gene function is described.

CONCLUSIONS

Genome-wide association studies represent a paradigm shift in the study of cardiovascular disease, providing identification of genes, cellular phenotypes, and disease pathways that empower the future of targeted drug development.

Recent advances in Forensic DNA Phenotyping of appearance, ancestry and age

Forensic DNA Phenotyping (FDP) comprises the prediction of a person's externally visible characteristics regarding appearance, biogeographic ancestry and age from DNA of crime scene samples, to provide investigative leads to help find unknown perpetrators that cannot be identified with forensic STR-profiling. In recent years, FDP has advanced considerably in all of its three components, which we summarize in this review article. Appearance prediction from DNA has broadened beyond eye, hair and skin color to additionally comprise other traits such as eyebrow color, freckles, hair structure, hair loss in men, and tall stature. Biogeographic ancestry inference from DNA has progressed from continental ancestry to sub-continental ancestry detection and the resolving of co-ancestry patterns in genetically admixed individuals. Age estimation from DNA has widened beyond blood to more somatic tissues such as saliva and bones as well as new markers and tools for semen. Technological progress has allowed forensically suitable DNA technology with largely increased multiplex capacity for the simultaneous analysis of hundreds of DNA predictors with targeted massively parallel sequencing (MPS). Forensically validated MPS-based FDP tools for predicting from crime scene DNA i) several appearance traits, ii) multi-regional ancestry, iii) several appearance traits together with multi-regional ancestry, and iv) age from different tissue types, are already available. Despite recent advances that will likely increase the impact of FDP in criminal casework in the near future, moving reliable appearance, ancestry and age prediction from crime scene DNA to the level of detail and accuracy police investigators may desire, requires further intensified scientific research together with technical developments and forensic validations as well as the necessary funding.

Genetic and clinical determinants of abdominal aortic diameter: genome-wide association studies, exome array data and Mendelian randomization study

Progressive dilation of the infrarenal aortic diameter is a consequence of the ageing process and is considered the main determinant of abdominal aortic aneurysm (AAA). We aimed to investigate the genetic and clinical determinants of abdominal aortic diameter (AAD). We conducted a meta-analysis of genome-wide association studies in 10 cohorts (n = 13 542) imputed to the 1000 Genome Project reference panel including 12 815 subjects in the discovery phase and 727 subjects [Partners Biobank cohort 1 (PBIO)] as replication. Maximum anterior-posterior diameter of the infrarenal aorta was used as AAD. We also included exome array data (n = 14 480) from seven epidemiologic studies. Single-variant and gene-based associations were done using SeqMeta package. A Mendelian randomization analysis was applied to investigate the causal effect of a number of clinical risk factors on AAD. In genome-wide association study (GWAS) on AAD, rs74448815 in the intronic region of LDLRAD4 reached genome-wide significance (beta = -0.02, SE = 0.004, P-value = 2.10 × 10-8). The association replicated in the PBIO1 cohort (P-value = 8.19 × 10-4). In exome-array single-variant analysis (P-value threshold = 9 × 10-7), the lowest P-value was found for rs239259 located in SLC22A20 (beta = 0.007, P-value = 1.2 × 10-5). In the gene-based analysis (P-value threshold = 1.85 × 10-6), PCSK5 showed an association with AAD (P-value = 8.03 × 10-7). Furthermore, in Mendelian randomization analyses, we found evidence for genetic association of pulse pressure (beta = -0.003, P-value = 0.02), triglycerides (beta = -0.16, P-value = 0.008) and height (beta = 0.03, P-value < 0.0001), known risk factors for AAA, consistent with a causal association with AAD. Our findings point to new biology as well as highlighting gene regions in mechanisms that have previously been implicated in the genetics of other vascular diseases.

Predicting Physical Appearance from DNA Data-Towards Genomic Solutions

The idea of forensic DNA intelligence is to extract from genomic data any information that can help guide the investigation. The clues to the externally visible phenotype are of particular practical importance. The high heritability of the physical phenotype suggests that genetic data can be easily predicted, but this has only become possible with less polygenic traits. The forensic community has developed DNA-based predictive tools by employing a limited number of the most important markers analysed with targeted massive parallel sequencing. The complexity of the genetics of many other appearance phenotypes requires big data coupled with sophisticated machine learning methods to develop accurate genomic predictors. A significant challenge in developing universal genomic predictive methods will be the collection of sufficiently large data sets. These should be created using whole-genome sequencing technology to enable the identification of rare DNA variants implicated in phenotype determination. It is worth noting that the correctness of the forensic sketch generated from the DNA data depends on the inclusion of an age factor. This, however, can be predicted by analysing epigenetic data. An important limitation preventing whole-genome approaches from being commonly used in forensics is the slow progress in the development and implementation of high-throughput, low DNA input sequencing technologies. The example of palaeoanthropology suggests that such methods may possibly be developed in forensics.

Atrial Fibrillation Genetics Update: Toward Clinical Implementation

Atrial fibrillation (AF) is the most common heart rhythm disorder worldwide and may have serious cardiovascular health consequences. AF is associated with increased risk of stroke, dementia, heart failure, and death. There are several known robust, clinical risk predictors for AF, such as male sex, increasing age, and hypertension; however, during the last couple of decades, a substantive genetic component has also been established. Over the last 10 years, the discovery of novel AF-related genetic variants has accelerated, increasing our understanding of mechanisms behind AF. Current studies are focusing on mapping the polygenic structure of AF, improving risk prediction, therapeutic development, and patient-specific management. Nevertheless, it is still difficult for clinicians to interpret the role of genetics in AF prediction and management. Here, we provide an overview of relevant topics within the genetics of AF and attempt to provide some guidance on how to interpret genetic advances and their implementation into clinical decision-making.

Update on the predictability of tall stature from DNA markers in Europeans

Predicting adult height from DNA has important implications in forensic DNA phenotyping. In 2014, we introduced a prediction model consisting of 180 height-associated SNPs based on data from 10,361 Northwestern Europeans enriched with tall individuals (770 > 1.88 standard deviation), which yielded a mid-ranged accuracy (AUC = 0.75 for binary prediction of tall stature and R² = 0.12 for quantitative prediction of adult height). Here, we provide an update on DNA-based height predictability considering an enlarged list of subsequently-published height-associated SNPs using data from the same set of 10,361 Europeans. A prediction model based on the full set of 689 SNPs showed an improved accuracy relative to previous models for both tall stature (AUC = 0.79) and quantitative height (R² = 0.21). A feature selection analysis revealed a subset of 412 most informative SNPs while the corresponding prediction model retained most of the accuracy (AUC = 0.76 and R² = 0.19) achieved with the full model. Over all, our study empirically exemplifies that the accuracy for predicting human appearance phenotypes with very complex underlying genetic architectures, such as adult height, can be improved by increasing the number of phenotype-associated DNA variants. Our work also demonstrates that a careful sub-selection allows for a considerable reduction of the number of DNA predictors that achieve similar prediction accuracy as provided by the full set. This is forensically relevant due to restrictions in the number of SNPs simultaneously analyzable with forensically suitable DNA technologies in the current days of targeted massively parallel sequencing in forensic genetics.

Predicting adult height from DNA variants in a European-Asian admixed population

Accurate genomic profiling for adult height is of high practical relevance in forensics genetics. Adult height is a classical reference trait in the field of human complex trait genetics characterized by highly polygenic nature and relatively high heritability. A meta-analysis of genome-wide association studies by the Genetic Investigation of Anthropocentric Traits (GIANT) consortium has identified 697 DNA variants associated with adult height in Europeans; however, whether these variants will still be informative in non-Europeans is still in question. The present study investigated the predictive power of these 697 height-associated SNPs in 687 Uyghurs of European-Asian admixed origin. Among all GIANT SNPs, 11% showed nominally significant association (6.78 × 10^-4 < p < 0.05) with adult height in the Uyghur population and among the significant SNPs 77% of allele effects were in the same direction as those in Europeans reported in the GIANT study. Fitting linear and logistic models using a polygenic score consisting of all GIANT SNPs resulted in an 80-20 cross-validated mean R² of 10.08% (95% CI 3.16-18.40%) for quantitative height prediction and a mean AUC value of 0.65 (95% CI 0.57-0.72%) for qualitative "above average" prediction. Fine-tuning the SNP set using their association p values considerably improved the prediction results (number of SNPs = 62, R² = 15.59%, 95% CI 6.80-25.71%; AUC = 0.70, 95% CI 62-0.77) in the Uyghurs. Overall, our findings demonstrate substantial differences between the European and Asian populations in the genetics of adult height, emphasizing the importance of population heterogeneity underlying the genetic architecture of adult height.

Common DNA Variants Accurately Rank an Individual of Extreme Height

Polygenic scores (or genetic risk scores) quantify the aggregate of small effects from many common genetic loci that have been associated with a trait through genome-wide association. Polygenic scores were first used successfully in schizophrenia and have since been applied to multiple phenotypes including multiple sclerosis, rheumatoid arthritis, and height. Because human height is an easily-measured and complex polygenic trait, polygenic height scores provide exciting insights into the predictability of aggregate common variant effect on the phenotype. Shawn Bradley is an extremely tall former professional basketball player from Brigham Young University and the National Basketball Association (NBA), measuring 2.29 meters (7′6^″, 99.99999th percentile for height) tall, with no known medical conditions. Here, we present a case where a rare combination of common SNPs in one individual results in an extremely high polygenic height score that is correlated with an extreme phenotype. While polygenic scores are not clinically significant in the average case, our findings suggest that for extreme phenotypes, polygenic scores may be more successful for the prediction of individuals.

Genome-wide compound heterozygote analysis highlights alleles associated with adult height in Europeans

Adult height is the most widely genetically studied common trait in humans; however, the trait variance explainable by currently known height-associated single nucleotide polymorphisms (SNPs) identified from the previous genome-wide association studies (GWAS) is yet far from complete given the high heritability of this complex trait. To exam if compound heterozygotes (CH) may explain extra height variance, we conducted a genome-wide analysis to screen for CH in association with adult height in 10,631 Dutch Europeans enriched with extremely tall people, using our recently developed method implemented in the software package CollapsABEL. The analysis identified six regions (3q23, 5q35.1, 6p21.31, 6p21.33, 7q21.2, and 9p24.3), where multiple pairs of SNPs as CH showed genome-wide significant association with height (P < 1.67 × 10⁻¹⁰). Of those, 9p24.3 represents a novel region influencing adult height, whereas the others have been highlighted in the previous GWAS on height based on analysis of individual SNPs. A replication analysis in 4080 Australians of European ancestry confirmed the significant CH-like association at 9p24.3 (P < 0.05). Together, the collapsed genotypes at these six loci explained 2.51% of the height variance (after adjusting for sex and age), compared with 3.23% explained by the 14 top-associated SNPs at 14 loci identified by traditional GWAS in the same data set (P < 5 × 10⁻⁸). Overall, our study empirically demonstrates that CH plays an important role in adult height and may explain a proportion of its “missing heritability”. Moreover, our findings raise promising expectations for other highly polygenic complex traits to explain missing heritability identifiable through CH-like associations.

MANAGEMENT OF ENDOCRINE DISEASE: Diagnostic and therapeutic approach of tall stature

Tall stature is defined as a height of more than 2 standard deviations (s.d.) above average for same sex and age. Tall individuals are usually referred to endocrinologists so that hormonal disorders leading to abnormal growth are excluded. However, the majority of these patients have familial tall stature or constitutional advance of growth (generally associated with obesity), both of which are diagnoses of exclusion. It is necessary to have familiarity with a large number of rarer overgrowth syndromes, especially because some of them may have severe complications such as aortic aneurysm, thromboembolism and tumor predisposition and demand-specific follow-up approaches. Additionally, endocrine disorders associated with tall stature have specific treatments and for this reason their recognition is mandatory. With this review, we intend to provide an up-to-date summary of the genetic conditions associated with overgrowth to emphasize a practical diagnostic approach of patients with tall stature and to discuss the limitations of current growth interruption treatment options.

Analysis of growth hormone receptor gene expression in tall and short stature children

BACKGROUND

The majority of children who present for evaluation of tall stature fall under the diagnosis of constitutional tall stature (CTS).

METHODS

To investigate mechanisms of tall stature, we evaluated serum IGF-I values and the expression of the GHR gene in the peripheral blood cells of 46 subjects with normal height, 38 with tall stature and 30 healthy children with short stature.

RESULTS

Our results showed significantly lower IGF-I levels in children with short stature (-0.57±0.18 SDS) compared to control children (0.056±0.19 SDS; p<0.0001) and to subjects with tall stature (0.594±0.17; p=0.00067). Furthermore, we found significantly higher GHR gene expression levels in tall children (321.84±90.04 agGHR/5×105agGAPDH) compared with other groups of subjects (short children: 30.13±7.5 agGHR/5×105agGAPDH, p<0.0001; controls: 86.81ag±19.5 GHR/5×105agGAPDH, p=0.035). The GHR gene expression level in short children was significantly lower compared with control subjects (p=0.0068).

CONCLUSIONS

Significantly higher GHR gene expression levels in tall subjects suggests a sensitization of the GHR-IGF system leading to overgrowth in CTS.

The Effect of the Exon-3-Deleted Growth Hormone Receptor on Pegvisomant-Treated Acromegaly: A Systematic Review and Meta-Analysis

BACKGROUND

The common exon 3 deletion polymorphism of the growth hormone receptor (d3-GHR) is associated with disease severity in acromegaly patients. The GHR antagonist pegvisomant (PEGV) is highly effective in treating severe acromegaly. Response to PEGV treatment seems to be influenced by d3-GHR and appears to be more responsive to PEGV, although available results remain conflicting.

OBJECTIVE

To assess the influence of d3-GHR on the responsiveness of acromegaly patients to PEGV by compiling the evidence derived from the largest available studies.

DESIGN

A systematic review of the literature identified three published studies and one conference abstract. Acromegaly patients (n = 324, 49.7% d3-GHR carriers) were treated with either PEGV monotherapy or PEGV combined with long-acting somatostatin analogues and/or cabergoline. A meta-analysis of raw data from these studies was performed.

RESULTS

No significant effect of the d3-GHR was observed while bringing insulin-like growth factor I (IGF-I) levels below the upper limit of normal with PEGV, which was defined as the lowest IGF-I level during PEGV treatment (mean difference: -2.3%; 95% CI: -6.5 to 1.8, p = 0.270). The PEGV dose required to achieve the lowest IGF-I levels was also not significantly influenced by individuals carrying d3-GHR (mean difference: 4.1 mg weekly; 95% CI: -5.1 to 13.2, p = 0.385). For both outcomes, separate analysis of PEGV monotherapy and combination treatment gave similar results.

CONCLUSION

Our findings suggest that the d3-GHR polymorphism has no effect on biochemical disease control in acromegaly, as it is not of added value for either the prediction of PEGV responsiveness or the determination of the required PEGV dose.

Demonstration of Protein-Based Human Identification Using the Hair Shaft Proteome

Human identification from biological material is largely dependent on the ability to characterize genetic polymorphisms in DNA. Unfortunately, DNA can degrade in the environment, sometimes below the level at which it can be amplified by PCR. Protein however is chemically more robust than DNA and can persist for longer periods. Protein also contains genetic variation in the form of single amino acid polymorphisms. These can be used to infer the status of non-synonymous single nucleotide polymorphism alleles. To demonstrate this, we used mass spectrometry-based shotgun proteomics to characterize hair shaft proteins in 66 European-American subjects. A total of 596 single nucleotide polymorphism alleles were correctly imputed in 32 loci from 22 genes of subjects' DNA and directly validated using Sanger sequencing. Estimates of the probability of resulting individual non-synonymous single nucleotide polymorphism allelic profiles in the European population, using the product rule, resulted in a maximum power of discrimination of 1 in 12,500. Imputed non-synonymous single nucleotide polymorphism profiles from European-American subjects were considerably less frequent in the African population (maximum likelihood ratio = 11,000). The converse was true for hair shafts collected from an additional 10 subjects with African ancestry, where some profiles were more frequent in the African population. Genetically variant peptides were also identified in hair shaft datasets from six archaeological skeletal remains (up to 260 years old). This study demonstrates that quantifiable measures of identity discrimination and biogeographic background can be obtained from detecting genetically variant peptides in hair shaft protein, including hair from bioarchaeological contexts.

Development of a methylation marker set for forensic age estimation using analysis of public methylation data and the Agena Bioscience EpiTYPER system

Individual age estimation has the potential to provide key information that could enhance and extend DNA intelligence tools. Following predictive tests for externally visible characteristics developed in recent years, prediction of age could guide police investigations and improve the assessment of age-related phenotype expression patterns such as hair colour changes and early onset of male pattern baldness. DNA methylation at CpG positions has emerged as the most promising DNA tests to ascertain the individual age of the donor of a biological contact trace. Although different methodologies are available to detect DNA methylation, EpiTYPER technology (Agena Bioscience, formerly Sequenom) provides useful characteristics that can be applied as a discovery tool in localized regions of the genome. In our study, a total of twenty-two candidate genomic regions, selected from the assessment of publically available data from the Illumina HumanMethylation 450 BeadChip, had a total of 177 CpG sites with informative methylation patterns that were subsequently investigated in detail. From the methylation analyses made, a novel age prediction model based on a multivariate quantile regression analysis was built using the seven highest age-correlated loci of ELOVL2, ASPA, PDE4C, FHL2, CCDC102B, C1orf132 and chr16:85395429. The detected methylation levels in these loci provide a median absolute age prediction error of ±3.07years and a percentage of prediction error relative to the age of 6.3%. We report the predictive performance of the developed model using cross validation of a carefully age-graded training set of 725 European individuals and a test set of 52 monozygotic twin pairs. The multivariate quantile regression age predictor, using the CpG sites selected in this study, has been placed in the open-access Snipper forensic classification website.

Short and tall stature: a new paradigm emerges

In the past, the growth hormone (GH)-insulin-like growth factor 1 (IGF-1) axis was often considered to be the main system that regulated childhood growth and, therefore, determined short stature and tall stature. However, findings have now revealed that the GH-IGF-1 axis is just one of many regulatory systems that control chondrogenesis in the growth plate, which is the biological process that drives height gain. Consequently, normal growth in children depends not only on GH and IGF-1 but also on multiple hormones, paracrine factors, extracellular matrix molecules and intracellular proteins that regulate the activity of growth plate chondrocytes. Mutations in the genes that encode many of these local proteins cause short stature or tall stature. Similarly, genome-wide association studies have revealed that the normal variation in height seems to be largely due to genes outside the GH-IGF-1 axis that affect growth at the growth plate through a wide variety of mechanisms. These findings point to a new conceptual framework for understanding short and tall stature that is centred not on two particular hormones but rather on the growth plate, which is the structure responsible for height gain.

Diagnostic Work-up and Follow-up in Children with Tall Stature: A Simplified Algorithm for Clinical Practice

OBJECTIVE

No evidence-based guideline has been published about optimal referral criteria and diagnostic work-up for tall stature in children. The aim of our study was to describe auxological and clinical characteristics of a cohort of children referred for tall stature, to identify potential candidates for adult height reduction, and to use these observations for developing a simple algorithm for diagnostic work-up and follow-up in clinical practice.

METHODS

Data regarding family and medical history, auxological measurements, bone age development, physical examination, additional diagnostic work-up, and final diagnosis were collected from all children referred for tall stature, irrespective of their actual height standard deviation score (HSDS). Predicted adult height (PAH) was calculated in children above 10 years. Characteristics of patients with an indication for adult height reduction were determined.

RESULTS

Hundred thirty-two children (43 boys) with a mean ± SD age of 10.9±3.2 (range 0.5-16.9) years were included in the study. Fifty percent of the referred children had an HSDS ≤2.0 (n=66). Two pathological cases (1.5%) were found (HSDS 2.3 and 0.9). Tall children without pathology were diagnosed as idiopathic tall, further classified as familial tall stature (80%), constitutional advancement of growth (5%), or unexplained non-familial tall stature (15%). Of the 74 children in whom PAH was calculated, epiphysiodesis was considered in six (8%) and performed in four (5%) patients.

CONCLUSION

The incidence of pathology was very low in children referred for tall stature, and few children were potential candidates for adult height reduction. We propose a simple diagnostic algorithm for clinical practice.

Prediction of male-pattern baldness from genotypes

The global demand for products that effectively prevent the development of male-pattern baldness (MPB) has drastically increased. However, there is currently no established genetic model for the estimation of MPB risk. We conducted a prediction analysis using single-nucleotide polymorphisms (SNPs) identified from previous GWASs of MPB in a total of 2725 German and Dutch males. A logistic regression model considering the genotypes of 25 SNPs from 12 genomic loci demonstrates that early-onset MPB risk is predictable at an accuracy level of 0.74 when 14 SNPs were included in the model, and measured using the area under the receiver-operating characteristic curves (AUC). Considering age as an additional predictor, the model can predict normal MPB status in middle-aged and elderly individuals at a slightly lower accuracy (AUC 0.69-0.71) when 6-11 SNPs were used. A variance partitioning analysis suggests that 55.8% of early-onset MPB genetic liability can be explained by common autosomal SNPs and 23.3% by X-chromosome SNPs. For normal MPB status in elderly individuals, the proportion of explainable variance is lower (42.4% for autosomal and 9.8% for X-chromosome SNPs). The gap between GWAS findings and the variance partitioning results could be explained by a large body of common DNA variants with small effects that will likely be identified in GWAS of increased sample sizes. Although the accuracy obtained here has not reached a clinically desired level, our model was highly informative for up to 19% of Europeans, thus may assist decision making on early MPB intervention actions and in forensic investigations.

Evaluation of DNA variants associated with androgenetic alopecia and their potential to predict male pattern baldness

Androgenetic alopecia, known in men as male pattern baldness (MPB), is a very conspicuous condition that is particularly frequent among European men and thus contributes markedly to variation in physical appearance traits amongst Europeans. Recent studies have revealed multiple genes and polymorphisms to be associated with susceptibility to MPB. In this study, 50 candidate SNPs for androgenetic alopecia were analyzed in order to verify their potential to predict MPB. Significant associations were confirmed for 29 SNPs from chromosomes X, 1, 5, 7, 18 and 20. A simple 5-SNP prediction model and an extended 20-SNP model were developed based on a discovery panel of 305 males from various European populations fitting one of two distinct phenotype categories. The first category consisted of men below 50 years of age with significant baldness and the second; men aged 50 years or older lacking baldness. The simple model comprised the five best predictors: rs5919324 near AR, rs1998076 in the 20p11 region, rs929626 in EBF1, rs12565727 in TARDBP and rs756853 in HDAC9. The extended prediction model added 15 SNPs from five genomic regions that improved overall prevalence-adjusted predictive accuracy measured by area under the receiver characteristic operating curve (AUC). Both models were evaluated for predictive accuracy using a test set of 300 males reflecting the general European population. Applying a 65% probability threshold, high prediction sensitivity of 87.1% but low specificity of 42.4% was obtained in men aged <50 years. In men aged ≥50, prediction sensitivity was slightly lower at 67.7% while specificity reached 90%. Overall, the AUC=0.761 calculated for men at or above 50 years of age indicates these SNPs offer considerable potential for the application of genetic tests to predict MPB patterns, adding a highly informative predictive system to the emerging field of forensic analysis of externally visible characteristics.

Genetic risk of neurodegenerative diseases is associated with mild cognitive impairment and conversion to dementia

INTRODUCTION

Neurodegenerative diseases are a major cause of cognitive impairment and can ultimately lead to dementia. Genome-wide association studies have uncovered many genetic variants conferring risk of neurodegenerative diseases, but their role in cognitive impairment remains unexplored.

METHODS

In the prospective, population-based Rotterdam Study, 3605 nondemented persons aged ≥55 years were genotyped, screened for mild cognitive impairment (MCI) in 2002 to 2005 and underwent continuous follow-up for dementia until 2012. Weighted polygenic risk scores of genetic variants for Alzheimer's disease (AD), Parkinson's disease (PD), and the frontotemporal lobar degeneration/amyotrophic lateral sclerosis disease spectrum (FTLD/ALS) were constructed and investigated for association with MCI and the subsequent conversion to dementia.

RESULTS

In total, 360 (10.0%) persons had MCI, of whom 147 (4.1%) were amnestic and 213 (5.9%) nonamnestic. The AD risk score was associated with both MCI subtypes (odds ratio for all MCI 1.15 [95% CI, 1.03-1.28]), whereas PD and FTLD/ALS risk scores were associated only with nonamnestic MCI (odds ratios 1.15 [1.00-1.32] and 1.19 [1.03-1.37], respectively). The AD risk score, but not PD and FTLD/ALS risk scores, was associated with an increased risk of dementia (hazard ratio 1.55 [1.37-1.77]).

DISCUSSION

Genetic evidence supports the view that multiple neurodegenerative pathways lead to MCI and that the subsequent conversion to dementia, primarily of the AD subtype, is mainly due to the AD pathway(s).

Genome-wide association study identifies three novel genetic markers associated with elite endurance performance

To investigate the association between multiple single-nucleotide polymorphisms (SNPs), aerobic performance and elite endurance athlete status in Russians. By using GWAS approach, we examined the association between 1,140,419 SNPs and relative maximal oxygen consumption rate (V.O₂max) in 80 international-level Russian endurance athletes (46 males and 34 females). To validate obtained results, we further performed case-control studies by comparing the frequencies of the most significant SNPs (with P < 10⁻⁵-10⁻⁸) between 218 endurance athletes and opposite cohorts (192 Russian controls, 1367 European controls, and 230 Russian power athletes). Initially, six ‘endurance alleles’ were identified showing discrete associations with V.O₂max both in males and females. Next, case-control studies resulted in remaining three SNPs (NFIA-AS2 rs1572312, TSHR rs7144481, RBFOX1 rs7191721) associated with endurance athlete status. The C allele of the most significant SNP, rs1572312, was associated with high values of V.O₂max (males: P = 0.0051; females: P = 0.0005). Furthermore, the frequency of the rs1572312 C allele was significantly higher in elite endurance athletes (95.5%) in comparison with non-elite endurance athletes (89.8%, P = 0.0257), Russian (88.8%, P = 0.007) and European (90.6%, P = 0.0197) controls and power athletes (86.2%, P = 0.0005). The rs1572312 SNP is located on the nuclear factor I A antisense RNA 2 (NFIA-AS2) gene which is supposed to regulate the expression of the NFIA gene (encodes transcription factor involved in activation of erythropoiesis and repression of the granulopoiesis). Our data show that the NFIA-AS2 rs1572312, TSHR rs7144481 and RBFOX1 rs7191721 polymorphisms are associated with aerobic performance and elite endurance athlete status.