The genetic history of Scandinavia from the Roman Iron Age to the present.

We investigate a 2,000-year genetic transect through Scandinavia spanning the Iron Age to the present, based on 48 new and 249 published ancient genomes and genotypes from 16,638 modern individuals. We find regional variation in the timing and magnitude of gene flow from three sources: the eastern Baltic, the British-Irish Isles, and southern Europe. British-Irish ancestry was widespread in Scandinavia from the Viking period, whereas eastern Baltic ancestry is more localized to Gotland and central Sweden. In some regions, a drop in current levels of external ancestry suggests that ancient immigrants contributed proportionately less to the modern Scandinavian gene pool than indicated by the ancestry of genomes from the Viking and Medieval periods. Finally, we show that a north-south genetic cline that characterizes modern Scandinavians is mainly due to the differential levels of Uralic ancestry and that this cline existed in the Viking Age and possibly earlier.

Evolvability and trait function predict phenotypic divergence of plant populations.

Understanding the causes and limits of population divergence in phenotypic traits is a fundamental aim of evolutionary biology, with the potential to yield predictions of adaptation to environmental change. Reciprocal transplant experiments and the evaluation of optimality models suggest that local adaptation is common but not universal, and some studies suggest that trait divergence is highly constrained by genetic variances and covariances of complex phenotypes. We analyze a large database of population divergence in plants and evaluate whether evolutionary divergence scales positively with standing genetic variation within populations (evolvability), as expected if genetic constraints are evolutionarily important. We further evaluate differences in divergence and evolvability-divergence relationships between reproductive and vegetative traits and between selfing, mixed-mating, and outcrossing species, as these factors are expected to influence both patterns of selection and evolutionary potentials. Evolutionary divergence scaled positively with evolvability. Furthermore, trait divergence was greater for vegetative traits than for floral (reproductive) traits, but largely independent of the mating system. Jointly, these factors explained ~40% of the variance in evolutionary divergence. The consistency of the evolvability-divergence relationships across diverse species suggests substantial predictability of trait divergence. The results are also consistent with genetic constraints playing a role in evolutionary divergence.

Three modes of evolution?Remarks on rates of evolution and time scaling.

Rates of evolution get smaller when they are measured over longer time intervals. As first shown by Gingerich, rates of morphological change measured from fossil time series show a robust minus-one scaling with time span, implying that evolutionary changes are just as large when measured over a hundred years as when measured over a hundred-thousand years. On even longer time scales, however, the scaling shifts toward a minus-half exponent consistent with evolution behaving as Brownian motion, as commonly observed in phylogenetic comparative studies. Here, I discuss how such scaling patterns arise, and I derive the patterns expected from standard stochastic models of evolution. I argue that observed shifts cannot be easily explained by simple univariate models, but require shifts in mode of evolution as time scale is changing. To illustrate this idea, I present a hypothesis about three distinct, but connected, modes of evolution. I analyze the scaling patterns predicted from this, and use the results to discuss how rates of evolution should be measured and interpreted. I argue that distinct modes of evolution at different time scales act to decouple micro- and macroevolution, and criticize various attempts at extrapolating from one to the other.

Both Diet and Sociality Affect Primate Brain-Size Evolution.

Increased brain size in humans and other primates is hypothesized to confer cognitive benefits but brings costs associated with growing and maintaining energetically expensive neural tissue. Previous studies have argued that changes in either diet or levels of sociality led to shifts in brain size, but results were equivocal. Here we test these hypotheses using phylogenetic comparative methods designed to jointly account for and estimate the effects of adaptation and phylogeny. Using the largest current sample of primate brain and body sizes with observation error, complemented by newly compiled diet and sociality data, we show that both diet and sociality have influenced the evolution of brain size. Shifting from simple to more complex levels of sociality resulted in relatively larger brains, while shifting to a more folivorous diet led to relatively smaller brains. While our results support the role of sociality, they modify a range of ecological hypotheses centered on the importance of frugivory, and instead indicate that digestive costs associated with increased folivory may have resulted in relatively smaller brains. [adaptation; allometry; bayou; evolutionary trend; energetic constraints; phylogenetic comparative methods; primate brain size; Slouch; social-brain hypothesis.].

A Cautionary Note on "A Cautionary Note on the Use of Ornstein Uhlenbeck Models in Macroevolutionary Studies".

Models based on the Ornstein-Uhlenbeck process have become standard for the comparative study of adaptation. Cooper et al. (2016) have cast doubt on this practice by claiming statistical problems with fitting Ornstein-Uhlenbeck models to comparative data. Specifically, they claim that statistical tests of Brownian motion may have too high Type I error rates and that such error rates are exacerbated by measurement error. In this note, we argue that these results have little relevance to the estimation of adaptation with Ornstein-Uhlenbeck models for three reasons. First, we point out that Cooper et al. (2016) did not consider the detection of distinct optima (e.g. for different environments), and therefore did not evaluate the standard test for adaptation. Second, we show that consideration of parameter estimates, and not just statistical significance, will usually lead to correct inferences about evolutionary dynamics. Third, we show that bias due to measurement error can be corrected for by standard methods. We conclude that Cooper et al. (2016) have not identified any statistical problems specific to Ornstein-Uhlenbeck models, and that their cautions against their use in comparative analyses are unfounded and misleading. [adaptation, Ornstein-Uhlenbeck model, phylogenetic comparative method.].

Analyzing Disparity and Rates of Morphological Evolution with Model-Based Phylogenetic Comparative Methods.

Understanding variation in rates of evolution and morphological disparity is a goal of macroevolutionary research. In a phylogenetic comparative methods framework, we present three explicit models for linking the rate of evolution of a trait to the state of another evolving trait. This allows testing hypotheses about causal influences on rates of phenotypic evolution with phylogenetic comparative data. We develop a statistical framework for fitting the models with generalized least-squares regression and use this to discuss issues and limitations in the study of rates of evolution more generally. We show that the power to detect effects on rates of evolution is low in that even strong causal effects are unlikely to explain more than a few percent of observed variance in disparity. We illustrate the models and issues by testing if rates of beak-shape evolution in birds are influenced by brain size, as may be predicted from a Baldwin effect in which presumptively more behaviorally flexible large-brained species generate more novel selection on themselves leading to higher rates of evolution. From an analysis of morphometric data for 645 species, we find evidence that both macro- and microevolution of the beak are faster in birds with larger brains, but with the caveat that there are no consistent effects of relative brain size.[Baldwin effect; beak shape; behavioral drive; bird; brain size; disparity; phylogenetic comparative method; rate of evolution.].

A large cohort study of the effects of Lewis, ABO, 13 other blood groups, and secretor status on COVID-19 susceptibility, severity, and long COVID-19.

BACKGROUND: Previous studies have reported Blood type O to confer a lower risk of SARS-CoV-2 infection, while secretor status and other blood groups have been suspected to have a similar effect as well. STUDY DESIGN AND METHODS: To determine whether any other blood groups influence testing positive for SARS-CoV-2, COVID-19 severity, or prolonged COVID-19, we used a large cohort of 650,156 Danish blood donors with varying available data for secretor status and blood groups ABO, Rh, Colton, Duffy, Diego, Dombrock, Kell, Kidd, Knops, Lewis, Lutheran, MNS, P1PK, Vel, and Yt. Of these, 36,068 tested positive for SARS-CoV-2 whereas 614,088 tested negative between 2020-02-17 and 2021-08-04. Associations between infection and blood groups were assessed using logistic regression models with sex and age as covariates. RESULTS: The Lewis blood group antigen Lea displayed strongly reduced SARS-CoV-2 susceptibility OR 0.85 CI[0.79-0.93] p < .001. Compared to blood type O, the blood types B, A, and AB were found more susceptible toward infection with ORs 1.1 CI[1.06-1.14] p < .001, 1.17 CI[1.14-1.2] p < .001, and 1.2 CI[1.14-1.26] p < .001, respectively. No susceptibility associations were found for the other 13 blood groups investigated. There was no association between any blood groups and COVID-19 hospitalization or long COVID-19. No secretor status associations were found. DISCUSSION: This study uncovers a new association to reduced SARS-CoV-2 susceptibility for Lewis type Lea and confirms the previous link to blood group O. The new association to Lea could be explained by a link between mucosal microbiome and SARS-CoV-2.

Genetic prediction of 33 blood group phenotypes using an existing genotype dataset.

BACKGROUND: Accurate blood type data are essential for blood bank management, but due to costs, few of 43 blood group systems are routinely determined in Danish blood banks. However, a more comprehensive dataset of blood types is useful in scenarios such as rare blood type allocation. We aimed to investigate the viability and accuracy of predicting blood types by leveraging an existing dataset of imputed genotypes for two cohorts of approximately 90,000 each (Danish Blood Donor Study and Copenhagen Biobank) and present a more comprehensive overview of blood types for our Danish donor cohort. STUDY DESIGN AND METHODS: Blood types were predicted from genome array data using known variant determinants. Prediction accuracy was confirmed by comparing with preexisting serological blood types. The Vel blood group was used to test the viability of using genetic prediction to narrow down the list of candidate donors with rare blood types. RESULTS: Predicted phenotypes showed a high balanced accuracy >99.5% in most cases: A, B, C/c, Coa /Cob , Doa /Dob , E/e, Jka /Jkb , Kna /Knb , Kpa /Kpb , M/N, S/s, Sda , Se, and Yta /Ytb , while some performed slightly worse: Fya /Fyb , K/k, Lua /Lub , and Vel ~99%-98% and CW and P1 ~96%. Genetic prediction identified 70 potential Vel negatives in our cohort, 64 of whom were confirmed correct using polymerase chain reaction (negative predictive value: 91.5%). DISCUSSION: High genetic prediction accuracy in most blood groups demonstrated the viability of generating blood types using preexisting genotype data at no cost and successfully narrowed the pool of potential individuals with the rare Vel-negative phenotype from 180,000 to 70.

Genome-wide association study of febrile seizures implicates fever response and neuronal excitability genes.

Febrile seizures represent the most common type of pathological brain activity in young children and are influenced by genetic, environmental and developmental factors. In a minority of cases, febrile seizures precede later development of epilepsy. We conducted a genome-wide association study of febrile seizures in 7635 cases and 83 966 controls identifying and replicating seven new loci, all with P < 5 × 10-10. Variants at two loci were functionally related to altered expression of the fever response genes PTGER3 and IL10, and four other loci harboured genes (BSN, ERC2, GABRG2, HERC1) influencing neuronal excitability by regulating neurotransmitter release and binding, vesicular transport or membrane trafficking at the synapse. Four previously reported loci (SCN1A, SCN2A, ANO3 and 12q21.33) were all confirmed. Collectively, the seven novel and four previously reported loci explained 2.8% of the variance in liability to febrile seizures, and the single nucleotide polymorphism heritability based on all common autosomal single nucleotide polymorphisms was 10.8%. GABRG2, SCN1A and SCN2A are well-established epilepsy genes and, overall, we found positive genetic correlations with epilepsies (rg = 0.39, P = 1.68 × 10-4). Further, we found that higher polygenic risk scores for febrile seizures were associated with epilepsy and with history of hospital admission for febrile seizures. Finally, we found that polygenic risk of febrile seizures was lower in febrile seizure patients with neuropsychiatric disease compared to febrile seizure patients in a general population sample. In conclusion, this largest genetic investigation of febrile seizures to date implicates central fever response genes as well as genes affecting neuronal excitability, including several known epilepsy genes. Further functional and genetic studies based on these findings will provide important insights into the complex pathophysiological processes of seizures with and without fever.

Mutation predicts 40 million years of fly wing evolution.

Mutation enables evolution, but the idea that adaptation is also shaped by mutational variation is controversial. Simple evolutionary hypotheses predict such a relationship if the supply of mutations constrains evolution, but it is not clear that constraints exist, and, even if they do, they may be overcome by long-term natural selection. Quantification of the relationship between mutation and phenotypic divergence among species will help to resolve these issues. Here we use precise data on over 50,000 Drosophilid fly wings to demonstrate unexpectedly strong positive relationships between variation produced by mutation, standing genetic variation, and the rate of evolution over the last 40 million years. Our results are inconsistent with simple constraint hypotheses because the rate of evolution is very low relative to what both mutational and standing variation could allow. In principle, the constraint hypothesis could be rescued if the vast majority of mutations are so deleterious that they cannot contribute to evolution, but this also requires the implausible assumption that deleterious mutations have the same pattern of effects as potentially advantageous ones. Our evidence for a strong relationship between mutation and divergence in a slowly evolving structure challenges the existing models of mutation in evolution.

Genome-wide association study identifies 16 genomic regions associated with circulating cytokines at birth.

Circulating inflammatory markers are essential to human health and disease, and they are often dysregulated or malfunctioning in cancers as well as in cardiovascular, metabolic, immunologic and neuropsychiatric disorders. However, the genetic contribution to the physiological variation of levels of circulating inflammatory markers is largely unknown. Here we report the results of a genome-wide genetic study of blood concentration of ten cytokines, including the hitherto unexplored calcium-binding protein (S100B). The study leverages a unique sample of neonatal blood spots from 9,459 Danish subjects from the iPSYCH initiative. We estimate the SNP-heritability of marker levels as ranging from essentially zero for Erythropoietin (EPO) up to 73% for S100B. We identify and replicate 16 associated genomic regions (p < 5 x 10-9), of which four are novel. We show that the associated variants map to enhancer elements, suggesting a possible transcriptional effect of genomic variants on the cytokine levels. The identification of the genetic architecture underlying the basic levels of cytokines is likely to prompt studies investigating the relationship between cytokines and complex disease. Our results also suggest that the genetic architecture of cytokines is stable from neonatal to adult life.

Genetic Susceptibility Loci in Genomewide Association Study of Cluster Headache.

OBJECTIVE: Identifying common genetic variants that confer genetic risk for cluster headache. METHODS: We conducted a case-control study in the Dutch Leiden University Cluster headache neuro-Analysis program (LUCA) study population (n = 840) and unselected controls from the Netherlands Epidemiology of Obesity Study (NEO; n = 1,457). Replication was performed in a Norwegian sample of 144 cases from the Trondheim Cluster headache sample and 1,800 controls from the Nord-Trøndelag Health Survey (HUNT). Gene set and tissue enrichment analyses, blood cell-derived RNA-sequencing of genes around the risk loci and linkage disequilibrium score regression were part of the downstream analyses. RESULTS: An association was found with cluster headache for 4 independent loci (r2 < 0.1) with genomewide significance (p < 5 × 10-8 ), rs11579212 (odds ratio [OR] = 1.51, 95% confidence interval [CI] = 1.33-1.72 near RP11-815 M8.1), rs6541998 (OR = 1.53, 95% CI = 1.37-1.74 near MERTK), rs10184573 (OR = 1.43, 95% CI = 1.26-1.61 near AC093590.1), and rs2499799 (OR = 0.62, 95% CI = 0.54-0.73 near UFL1/FHL5), collectively explaining 7.2% of the variance of cluster headache. SNPs rs11579212, rs10184573, and rs976357, as proxy SNP for rs2499799 (r2  = 1.0), replicated in the Norwegian sample (p < 0.05). Gene-based mapping yielded ASZ1 as possible fifth locus. RNA-sequencing indicated differential expression of POLR1B and TMEM87B in cluster headache patients. INTERPRETATION: This genomewide association study (GWAS) identified and replicated genetic risk loci for cluster headache with effect sizes larger than those typically seen in complex genetic disorders. ANN NEUROL 2021;90:203-216.

Hyperhidrosis and human leucocyte antigens in the Danish Blood Donor Study.

Familial clustering of the skin disease primary hyperhidrosis suggests a genetic component to the disease. The human leucocyte antigen (HLA) is implicated in a range of diseases, including many comorbidities to hyperhidrosis. No study has investigated whether the HLA genes are involved in the pathogenesis of hyperhidrosis. We, therefore, compared HLA alleles in individuals with and without hyperhidrosis in this study of 65 000 blood donors. In this retrospective cohort study, we retrieved information on individuals with and without hyperhidrosis using self-reported questionnaires, the Danish National Patient Registry and the Danish National Prescription Registry on participants recruited to the Danish Blood Donor Study between 2010 and 2019. Association tests using logistic regression were conducted for each HLA allele corrected for sex, age, body mass index, smoking and principal components. Overall, 145 of 65 795 (0.2%) participants had hospital diagnosed hyperhidrosis. Similarly, 1379 of 15 530 (8.9%) participants had moderate-severe self-reported hyperhidrosis, of whom 447 (2.9%) had severe self-reported hyperhidrosis. Altogether, 28 participants had both hospital diagnosed and moderate-severe self-reported hyperhidrosis. Severe self-reported hyperhidrosis was associated with HLA-A*80:01 (adjusted odds ratio 26.97; 95% confidence interval 5.32-136.70; n = 7; P < .001). Moderate-severe self-reported hyperhidrosis and hospital diagnosed hyperhidrosis were not associated with any HLA. The association between hyperhidrosis and HLA-A*80:01 was based on a very small number of cases and not replicated in other patient subsets, and therefore likely a chance finding. Thus, this study suggests that genes other than the HLA are involved in the pathogenesis of hyperhidrosis.

Smooth muscle ATP-sensitive potassium channels mediate migraine-relevant hypersensitivity in mouse models.

BACKGROUND: Opening of KATP channels by systemic levcromakalim treatment triggers attacks in migraine patients and hypersensitivity to von Frey stimulation in a mouse model. Blocking of these channels is effective in several preclinical migraine models. It is unknown in what tissue and cell type KATP-induced migraine attacks are initiated and which KATP channel subtype is targeted. METHODS: In mouse models, we administered levcromakalim intracerebroventricularly, intraperitoneally and intraplantarily and compared the nociceptive responses by von Frey and hotplate tests. Mice with a conditional loss-of-function mutation in the smooth muscle KATP channel subunit Kir6.1 were given levcromakalim and GTN and examined with von Frey filaments. Arteries were tested for their ability to dilate ex vivo. mRNA expression, western blotting and immunohistochemical stainings were made to identify relevant target tissue for migraine induced by KATP channel opening. RESULTS: Systemic administration of levcromakalim induced hypersensitivity but central and local administration provided antinociception respectively no effect. The Kir6.1 smooth muscle knockout mouse was protected from both GTN and levcromakalim induced hypersensitivity, and their arteries had impaired dilatory response to the latter. mRNA and protein expression studies showed that trigeminal ganglia did not have significant KATP channel expression of any subtype, whereas brain arteries and dura mater primarily expressed the Kir6.1 + SUR2B subtype. CONCLUSION: Hypersensitivity provoked by GTN and levcromakalim in mice is dependent on functional smooth muscle KATP channels of extracerebral origin. These results suggest a vascular contribution to hypersensitivity induced by migraine triggers.

Measuring flow speeds in natural waters by training an artificial neural network to analyze high-frequency flow-induced vibrations of tethered floats.

Measuring water currents in natural waters is limited by the cost of sensors. Standard sonar-based acoustic current Doppler profilers (ADCPs) are high cost, about $10-20 K per unit. Tilt current meters (TCMs) are much cheaper. They consist of a bottom-mounted subsurface float equipped with an inertial measurement unit (IMU) and data center that records the float's motion and attitude as a time series. The flow speed is measured by calculating the tilt angle of the float in response to the current. However, tilt-based measurements require the float system to be carefully engineered and its physical response optimized for good results. Even so, high-frequency flow-induced vibrations often dominate the motion and must be averaged and filtered out of the data and discarded. This represents the loss of potentially valuable information, but decoding the high-frequency components for such useful data is difficult. These experiments explored using an artificial neural network (ANN) approach to extract the ambient water current speed from that high-frequency data alone, after the displacement information was filtered out. The methods were informed by the ANN designs and data augmentation techniques used by neurologists to observe the tremors and other motions exhibited by patients experiencing symptoms of Parkinson's disease. Once the model was trained using carefully selected training and validation sets to prevent overfitting, the results of evaluating previously unseen data by the model are clear and promising. Water current speed was accurately calculated from the high-frequency components of the motion sensor data and agreed with corresponding current speeds measured by established methods. This novel approach could facilitate new sensor system designs that can be empirically or self-calibrated more efficiently and have a lower barrier to application than those currently available.

Epidemiology of Hyperhidrosis in Danish Blood Donors.

The risk factors and disease implications of hyper-hidrosis are unknown. The objectives of this retrospective cohort study were to estimate the prevalence of hyperhidrosis and to compare demographic, life-style, and socioeconomic parameters in blood donors with and without self-reported or hospital-diagnosed hyperhidrosis. The study included blood donors from the Danish Blood Donor Study for the period 2010-2019. Registry data were collected from Statistics Denmark. Overall, 2,794 of 30,808 blood donors (9.07%; 95% confidence interval (95% CI) 8.75-9.40) had self- reported hyperhidrosis and 284 of 122,225 (0.23%; 95% CI 0.21-0.26) had hospital-diagnosed hyperhidrosis. Self-reported hyperhidrosis was associated with smoking (odds ratio (OR) 1.17; 95% CI 1.05-1.31), overweight (OR 1.72; 95% CI 1.58-1.87), "unemployed" (OR 1.60; 95% CI 1.24-2.08), "short education" (OR 0.76; 95% CI 0.64-0.90), and lower income (beta-coefficient -26,121; 95% CI -37,931, -14,311). Hospital-diagnosed hyperhidrosis did not differ from controls. Thus, self-reported hyperhidrosis was associated with potential hyperhidrosis risk factors (smoking, overweight) and disease implications (unemployment, low education level and income).

Genetic variability in the absorption of dietary sterols affects the risk of coronary artery disease.

AIMS: To explore whether variability in dietary cholesterol and phytosterol absorption impacts the risk of coronary artery disease (CAD) using as instruments sequence variants in the ABCG5/8 genes, key regulators of intestinal absorption of dietary sterols. METHODS AND RESULTS: We examined the effects of ABCG5/8 variants on non-high-density lipoprotein (non-HDL) cholesterol (N up to 610 532) and phytosterol levels (N = 3039) and the risk of CAD in Iceland, Denmark, and the UK Biobank (105 490 cases and 844 025 controls). We used genetic scores for non-HDL cholesterol to determine whether ABCG5/8 variants confer greater risk of CAD than predicted by their effect on non-HDL cholesterol. We identified nine rare ABCG5/8 coding variants with substantial impact on non-HDL cholesterol. Carriers have elevated phytosterol levels and are at increased risk of CAD. Consistent with impact on ABCG5/8 transporter function in hepatocytes, eight rare ABCG5/8 variants associate with gallstones. A genetic score of ABCG5/8 variants predicting 1 mmol/L increase in non-HDL cholesterol associates with two-fold increase in CAD risk [odds ratio (OR) = 2.01, 95% confidence interval (CI) 1.75-2.31, P = 9.8 × 10-23] compared with a 54% increase in CAD risk (OR = 1.54, 95% CI 1.49-1.59, P = 1.1 × 10-154) associated with a score of other non-HDL cholesterol variants predicting the same increase in non-HDL cholesterol (P for difference in effects = 2.4 × 10-4). CONCLUSIONS: Genetic variation in cholesterol absorption affects levels of circulating non-HDL cholesterol and risk of CAD. Our results indicate that both dietary cholesterol and phytosterols contribute directly to atherogenesis.

Echocardiography improves prediction of major adverse cardiovascular events in a population with type 1 diabetes and without known heart disease: the Thousand & 1 Study.

AIMS/HYPOTHESIS: Cardiovascular disease is the most common comorbidity in type 1 diabetes. However, current guidelines do not include routine assessment of myocardial function. We investigated whether echocardiography provides incremental prognostic information in individuals with type 1 diabetes without known heart disease. METHODS: A prospective cohort of individuals with type 1 diabetes without known heart disease was recruited from the outpatient clinic. Follow-up was performed through Danish national registers. The association of echocardiography with major adverse cardiovascular events (MACE) and the incremental prognostic value when added to the clinical Steno T1D Risk Engine were examined. RESULTS: A total of 1093 individuals were included: median (interquartile range) age 50.2 (39.2-60.3) years and HbA1c 65 (56-74) mmol/mol; 53% men; and mean (SD) BMI 25.5 (3.9) kg/m2 and diabetes duration 25.8 (14.6) years. During 7.5 years of follow-up, 145 (13.3%) experienced MACE. Echocardiography significantly and independently predicted MACE: left ventricular ejection fraction (LVEF) <45% (n = 18) vs ≥45% (n = 1075), HR (95% CI) 3.93 (1.91, 8.08), p < 0.001; impaired global longitudinal strain (GLS), 1.65 (1.17, 2.34) (n = 263), p = 0.005; diastolic mitral early velocity (E)/early diastolic tissue Doppler velocity (e') <8 (n = 723) vs E/e' 8-12 (n = 285), 1.59 (1.04, 2.42), p = 0.031; and E/e' <8 vs E/e' ≥12 (n = 85), 2.30 (1.33, 3.97), p = 0.003. In individuals with preserved LVEF (n = 1075), estimates for impaired GLS were 1.49 (1.04, 2.15), p = 0.032; E/e' <8 vs E/e' 8-12, 1.61 (1.04, 2.49), p = 0.033; and E/e' <8 vs E/e' ≥12, 2.49 (1.41, 4.37), p = 0.001. Adding echocardiographic variables to the Steno T1D Risk Engine significantly improved risk prediction: Harrell's C statistic, 0.791 (0.757, 0.824) vs 0.780 (0.746, 0.815), p = 0.027; and net reclassification index, 52%, p < 0.001. CONCLUSIONS/INTERPRETATION: In individuals with type 1 diabetes without known heart disease, echocardiography significantly improves risk prediction over and above guideline-recommended clinical risk factors alone and could have a role in clinical care.

Millions of Years Behind: Slow Adaptation of Ruminants to Grasslands.

The Late Cretaceous appearance of grasses, followed by the Cenozoic advancement of grasslands as dominant biomes, has contributed to the evolution of a range of specialized herbivores adapted to new diets, as well as to increasingly open and arid habitats. Many mammals including ruminants, the most diversified ungulate suborder, evolved high-crowned (hypsodont) teeth as an adaptation to tooth-wearing diets and habitats. The impact of different causes of tooth wear is still a matter of debate, and the temporal pattern of hypsodonty evolution in relation to the evolution of grasslands remains unclear. We present an improved time-calibrated molecular phylogeny of Cetartiodactyla, with phylogenetic reconstruction of ancestral ruminant diets and habitats, based on characteristics of extant taxa. Using this timeline, as well as the fossil record of grasslands, we conduct phylogenetic comparative analyses showing that hypsodonty in ruminants evolved as an adaptation to both diet and habitat. Our results demonstrate a slow, perhaps constrained, evolution of hypsodonty toward estimated optimal states, excluding the possibility of immediate adaptation. This augments recent findings that slow adaptation is not uncommon on million-year time scales.

Comparing migraine with and without aura to healthy controls using RNA sequencing.

BACKGROUND: Migraine mechanisms are *These authors contributed equally to this work. only partly known. Some studies have previously described genes differentially expressed between blood from migraineurs and controls. The objective of this study was to describe gene expression in subtypes of migraine outside of attack and in healthy controls. METHODS: We extensively phenotyped 17 migraine without aura and nine migraine with aura female patients, and 20 age-matched female controls. Cubital venous blood was RNA sequenced. Genes differentially expressed between migraineurs (migraine without aura and migraine with aura) and controls, and between migraine without aura and migraine with aura were identified using a case-control design. A co-expression network was constructed to investigate the difference between migraineurs and healthy controls at the network level. RESULTS: We found two differentially expressed genes: NMNAT2 and RETN. Both were differentially expressed between migraine with aura and controls, but they could not be replicated in an independent cohort. Co-expression network analysis resulted in one cluster of highly interconnected genes that was nominally significantly associated with migraine; however, no pathways or gene ontology terms were detected. CONCLUSIONS: We showed no clear distinct difference in gene expression profiles of peripheral blood of migraineurs and controls and were not able to replicate findings from previous studies. A larger sample size may be needed to detect minor differences.