GDF15 linked to maternal risk of nausea and vomiting during pregnancy.

GDF15, a hormone acting on the brainstem, has been implicated in the nausea and vomiting of pregnancy, including its most severe form, hyperemesis gravidarum (HG), but a full mechanistic understanding is lacking1-4. Here we report that fetal production of GDF15 and maternal sensitivity to it both contribute substantially to the risk of HG. We confirmed that higher GDF15 levels in maternal blood are associated with vomiting in pregnancy and HG. Using mass spectrometry to detect a naturally labelled GDF15 variant, we demonstrate that the vast majority of GDF15 in the maternal plasma is derived from the feto-placental unit. By studying carriers of rare and common genetic variants, we found that low levels of GDF15 in the non-pregnant state increase the risk of developing HG. Conversely, women with ß-thalassaemia, a condition in which GDF15 levels are chronically high5, report very low levels of nausea and vomiting of pregnancy. In mice, the acute food intake response to a bolus of GDF15 is influenced bi-directionally by prior levels of circulating GDF15 in a manner suggesting that this system is susceptible to desensitization. Our findings support a putative causal role for fetally derived GDF15 in the nausea and vomiting of human pregnancy, with maternal sensitivity, at least partly determined by prepregnancy exposure to the hormone, being a major influence on its severity. They also suggest mechanism-based approaches to the treatment and prevention of HG.

Author Correction: A massive core for a cluster of galaxies at a redshift of 4.3.

Change history: In this Letter, the Acknowledgements section should have included the following sentence: "The National Radio Astronomy Observatory is a facility of the National Science Foundation operated under cooperative agreement by Associated Universities, Inc.". This omission has been corrected online.

A massive core for a cluster of galaxies at a redshift of 4.3.

Massive galaxy clusters have been found that date to times as early as three billion years after the Big Bang, containing stars that formed at even earlier epochs1-3. The high-redshift progenitors of these galaxy clusters-termed 'protoclusters'-can be identified in cosmological simulations that have the highest overdensities (greater-than-average densities) of dark matter4-6. Protoclusters are expected to contain extremely massive galaxies that can be observed as luminous starbursts 7 . However, recent detections of possible protoclusters hosting such starbursts8-11 do not support the kind of rapid cluster-core formation expected from simulations 12 : the structures observed contain only a handful of starbursting galaxies spread throughout a broad region, with poor evidence for eventual collapse into a protocluster. Here we report observations of carbon monoxide and ionized carbon emission from the source SPT2349-56. We find that this source consists of at least 14 gas-rich galaxies, all lying at redshifts of 4.31. We demonstrate that each of these galaxies is forming stars between 50 and 1,000 times more quickly than our own Milky Way, and that all are located within a projected region that is only around 130 kiloparsecs in diameter. This galaxy surface density is more than ten times the average blank-field value (integrated over all redshifts), and more than 1,000 times the average field volume density. The velocity dispersion (approximately 410 kilometres per second) of these galaxies and the enormous gas and star-formation densities suggest that this system represents the core of a cluster of galaxies that was already at an advanced stage of formation when the Universe was only 1.4 billion years old. A comparison with other known protoclusters at high redshifts shows that SPT2349-56 could be building one of the most massive structures in the Universe today.

Galaxy growth in a massive halo in the first billion years of cosmic history.

According to the current understanding of cosmic structure formation, the precursors of the most massive structures in the Universe began to form shortly after the Big Bang, in regions corresponding to the largest fluctuations in the cosmic density field. Observing these structures during their period of active growth and assembly-the first few hundred million years of the Universe-is challenging because it requires surveys that are sensitive enough to detect the distant galaxies that act as signposts for these structures and wide enough to capture the rarest objects. As a result, very few such objects have been detected so far. Here we report observations of a far-infrared-luminous object at redshift 6.900 (less than 800 million years after the Big Bang) that was discovered in a wide-field survey. High-resolution imaging shows it to be a pair of extremely massive star-forming galaxies. The larger is forming stars at a rate of 2,900 solar masses per year, contains 270 billion solar masses of gas and 2.5 billion solar masses of dust, and is more massive than any other known object at a redshift of more than 6. Its rapid star formation is probably triggered by its companion galaxy at a projected separation of 8 kiloparsecs. This merging companion hosts 35 billion solar masses of stars and has a star-formation rate of 540 solar masses per year, but has an order of magnitude less gas and dust than its neighbour and physical conditions akin to those observed in lower-metallicity galaxies in the nearby Universe. These objects suggest the presence of a dark-matter halo with a mass of more than 100 billion solar masses, making it among the rarest dark-matter haloes that should exist in the Universe at this epoch.

Renal resistive index in patients supported with a durable continuous flow left ventricular assist device.

BACKGROUND: The impact of continuous flow resulting from contemporary left ventricular assist devices (LVAD) on renal vascular physiology is unknown. Renal resistive index (RRI) reflects arterial compliance, as well as renal vascular resistance, contributed by afferent and efferent arteriolar tone, the renal interstitium as well as renal venous pressures. METHODS: Prospective, single center study with renal Doppler evaluation at baseline (pre-implant) and at 3-months support. Outcomes assessed include need for post-operative renal replacement therapy (RRT), worsening renal function (WRF) defined as persistent increase from pre-implant KDIGO chronic kidney disease stage, right ventricular (RV) failure, and survival to transplantation. RESULTS: Pre-implant RRI did not predict cardiorenal outcomes including right heart failure, need for renal replacement therapy or worsening renal function. Post-implant RRI was significantly lower than pre-implant RRI, with a distinct Doppler waveform characteristic of continuous flow. Post-implant renal end-diastolic velocity, but not RRI, correlated strongly with LVAD flow (Spearman rho -0.99, p < 0.001), with trend toward correlation with mean arterial pressure (Spearman's rho 0.63, p = 0.129). There was a negative correlation between post-implant RRI and mean pulmonary artery pressure (Spearman's rho -0.81, p = 0.049), likely driven by elevated pulmonary capillary wedge pressure (Spearman's rho -0.83, p = 0.058). CONCLUSION: The hemodynamic contributors to RRI in LVAD supported patients are complex. Higher mean pulmonary artery and pulmonary capillary wedge pressures seen in lower RRI may reflect a smaller difference in systolic and diastolic flow. Future simultaneous Doppler assessment of the LVAD outflow graft and RRI may help understand the hemodynamic interactions contributing to this index.

Genome-wide meta-analysis identifies novel loci associated with free triiodothyronine and thyroid-stimulating hormone.

PURPOSE: Thyroid hormones are essential for the normal function of almost all human tissues, and have critical roles in metabolism, differentiation and growth. Free triiodothyronine (fT3), free thyroxine (fT4) and thyroid-stimulating hormone (TSH) levels are under strong genetic influence; however, most of the heritability is yet unexplained. METHODS: In order to identify novel loci associated with fT3, fT4 and TSH serum levels we performed a genome-wide meta-analysis of 7 411 206 polymorphisms in up to 1731 euthyroid individuals from three Croatian cohorts from Dalmatia region: two genetically isolated island populations and one mainland population. Additionally, we also performed a bivariate analysis of fT3 and fT4 levels. RESULTS: The EPHB2 gene variant rs67142165 reached genome-wide significance for association with fT3 plasma levels (P = 9.27 × 10-9) and its significance was confirmed in bivariate analysis (P = 9.72 × 10-9). We also found a genome-wide significant association for variant rs13037502 upstream of the PTPN1 gene and TSH plasma levels (P = 1.67 × 10-8). CONCLUSION: We identified a first genome-wide significant variant associated with fT3 plasma levels, as well as a novel locus associated with TSH plasma levels. These findings are biologically relevant and enrich our knowledge about the genetic basis of pituitary-thyroid axis function.

Genome-wide association study of alcohol consumption and genetic overlap with other health-related traits in UK Biobank (N=112 117).

Alcohol consumption has been linked to over 200 diseases and is responsible for over 5% of the global disease burden. Well-known genetic variants in alcohol metabolizing genes, for example, ALDH2 and ADH1B, are strongly associated with alcohol consumption but have limited impact in European populations where they are found at low frequency. We performed a genome-wide association study (GWAS) of self-reported alcohol consumption in 112 117 individuals in the UK Biobank (UKB) sample of white British individuals. We report significant genome-wide associations at 14 loci. These include single-nucleotide polymorphisms (SNPs) in alcohol metabolizing genes (ADH1B/ADH1C/ADH5) and two loci in KLB, a gene recently associated with alcohol consumption. We also identify SNPs at novel loci including GCKR, CADM2 and FAM69C. Gene-based analyses found significant associations with genes implicated in the neurobiology of substance use (DRD2, PDE4B). GCTA analyses found a significant SNP-based heritability of self-reported alcohol consumption of 13% (se=0.01). Sex-specific analyses found largely overlapping GWAS loci and the genetic correlation (rG) between male and female alcohol consumption was 0.90 (s.e.=0.09, P-value=7.16 × 10-23). Using LD score regression, genetic overlap was found between alcohol consumption and years of schooling (rG=0.18, s.e.=0.03), high-density lipoprotein cholesterol (rG=0.28, s.e.=0.05), smoking (rG=0.40, s.e.=0.06) and various anthropometric traits (for example, overweight, rG=-0.19, s.e.=0.05). This study replicates the association between alcohol consumption and alcohol metabolizing genes and KLB, and identifies novel gene associations that should be the focus of future studies investigating the neurobiology of alcohol consumption.

Assessing the genetic overlap between BMI and cognitive function.

Obesity and low cognitive function are associated with multiple adverse health outcomes across the life course. They have a small phenotypic correlation (r=-0.11; high body mass index (BMI)-low cognitive function), but whether they have a shared genetic aetiology is unknown. We investigated the phenotypic and genetic correlations between the traits using data from 6815 unrelated, genotyped members of Generation Scotland, an ethnically homogeneous cohort from five sites across Scotland. Genetic correlations were estimated using the following: same-sample bivariate genome-wide complex trait analysis (GCTA)-GREML; independent samples bivariate GCTA-GREML using Generation Scotland for cognitive data and four other samples (n=20 806) for BMI; and bivariate LDSC analysis using the largest genome-wide association study (GWAS) summary data on cognitive function (n=48 462) and BMI (n=339 224) to date. The GWAS summary data were also used to create polygenic scores for the two traits, with within- and cross-trait prediction taking place in the independent Generation Scotland cohort. A large genetic correlation of -0.51 (s.e. 0.15) was observed using the same-sample GCTA-GREML approach compared with -0.10 (s.e. 0.08) from the independent-samples GCTA-GREML approach and -0.22 (s.e. 0.03) from the bivariate LDSC analysis. A genetic profile score using cognition-specific genetic variants accounts for 0.08% (P=0.020) of the variance in BMI and a genetic profile score using BMI-specific variants accounts for 0.42% (P=1.9 × 10(-7)) of the variance in cognitive function. Seven common genetic variants are significantly associated with both traits at P<5 × 10(-5), which is significantly more than expected by chance (P=0.007). All these results suggest there are shared genetic contributions to BMI and cognitive function.

Genome-wide association study of cognitive functions and educational attainment in UK Biobank (N=112 151).

People's differences in cognitive functions are partly heritable and are associated with important life outcomes. Previous genome-wide association (GWA) studies of cognitive functions have found evidence for polygenic effects yet, to date, there are few replicated genetic associations. Here we use data from the UK Biobank sample to investigate the genetic contributions to variation in tests of three cognitive functions and in educational attainment. GWA analyses were performed for verbal-numerical reasoning (N=36 035), memory (N=112 067), reaction time (N=111 483) and for the attainment of a college or a university degree (N=111 114). We report genome-wide significant single-nucleotide polymorphism (SNP)-based associations in 20 genomic regions, and significant gene-based findings in 46 regions. These include findings in the ATXN2, CYP2DG, APBA1 and CADM2 genes. We report replication of these hits in published GWA studies of cognitive function, educational attainment and childhood intelligence. There is also replication, in UK Biobank, of SNP hits reported previously in GWA studies of educational attainment and cognitive function. GCTA-GREML analyses, using common SNPs (minor allele frequency>0.01), indicated significant SNP-based heritabilities of 31% (s.e.m.=1.8%) for verbal-numerical reasoning, 5% (s.e.m.=0.6%) for memory, 11% (s.e.m.=0.6%) for reaction time and 21% (s.e.m.=0.6%) for educational attainment. Polygenic score analyses indicate that up to 5% of the variance in cognitive test scores can be predicted in an independent cohort. The genomic regions identified include several novel loci, some of which have been associated with intracranial volume, neurodegeneration, Alzheimer's disease and schizophrenia.

Common polygenic risk for autism spectrum disorder (ASD) is associated with cognitive ability in the general population.

Cognitive impairment is common among individuals diagnosed with autism spectrum disorder (ASD) and attention-deficit hyperactivity disorder (ADHD). It has been suggested that some aspects of intelligence are preserved or even superior in people with ASD compared with controls, but consistent evidence is lacking. Few studies have examined the genetic overlap between cognitive ability and ASD/ADHD. The aim of this study was to examine the polygenic overlap between ASD/ADHD and cognitive ability in individuals from the general population. Polygenic risk for ADHD and ASD was calculated from genome-wide association studies of ASD and ADHD conducted by the Psychiatric Genetics Consortium. Risk scores were created in three independent cohorts: Generation Scotland Scottish Family Health Study (GS:SFHS) (n=9863), the Lothian Birth Cohorts 1936 and 1921 (n=1522), and the Brisbane Adolescent Twin Sample (BATS) (n=921). We report that polygenic risk for ASD is positively correlated with general cognitive ability (beta=0.07, P=6 × 10(-7), r(2)=0.003), logical memory and verbal intelligence in GS:SFHS. This was replicated in BATS as a positive association with full-scale intelligent quotient (IQ) (beta=0.07, P=0.03, r(2)=0.005). We did not find consistent evidence that polygenic risk for ADHD was associated with cognitive function; however, a negative correlation with IQ at age 11 years (beta=-0.08, Z=-3.3, P=0.001) was observed in the Lothian Birth Cohorts. These findings are in individuals from the general population, suggesting that the relationship between genetic risk for ASD and intelligence is partly independent of clinical state. These data suggest that common genetic variation relevant for ASD influences general cognitive ability.

Genome-wide analysis of over 106 000 individuals identifies 9 neuroticism-associated loci.

Neuroticism is a personality trait of fundamental importance for psychological well-being and public health. It is strongly associated with major depressive disorder (MDD) and several other psychiatric conditions. Although neuroticism is heritable, attempts to identify the alleles involved in previous studies have been limited by relatively small sample sizes. Here we report a combined meta-analysis of genome-wide association study (GWAS) of neuroticism that includes 91 370 participants from the UK Biobank cohort, 6659 participants from the Generation Scotland: Scottish Family Health Study (GS:SFHS) and 8687 participants from a QIMR (Queensland Institute of Medical Research) Berghofer Medical Research Institute (QIMR) cohort. All participants were assessed using the same neuroticism instrument, the Eysenck Personality Questionnaire-Revised (EPQ-R-S) Short Form's Neuroticism scale. We found a single-nucleotide polymorphism-based heritability estimate for neuroticism of ∼15% (s.e.=0.7%). Meta-analysis identified nine novel loci associated with neuroticism. The strongest evidence for association was at a locus on chromosome 8 (P=1.5 × 10(-15)) spanning 4 Mb and containing at least 36 genes. Other associated loci included interesting candidate genes on chromosome 1 (GRIK3 (glutamate receptor ionotropic kainate 3)), chromosome 4 (KLHL2 (Kelch-like protein 2)), chromosome 17 (CRHR1 (corticotropin-releasing hormone receptor 1) and MAPT (microtubule-associated protein Tau)) and on chromosome 18 (CELF4 (CUGBP elav-like family member 4)). We found no evidence for genetic differences in the common allelic architecture of neuroticism by sex. By comparing our findings with those of the Psychiatric Genetics Consortia, we identified a strong genetic correlation between neuroticism and MDD and a less strong but significant genetic correlation with schizophrenia, although not with bipolar disorder. Polygenic risk scores derived from the primary UK Biobank sample captured ∼1% of the variance in neuroticism in the GS:SFHS and QIMR samples, although most of the genome-wide significant alleles identified within a UK Biobank-only GWAS of neuroticism were not independently replicated within these cohorts. The identification of nine novel neuroticism-associated loci will drive forward future work on the neurobiology of neuroticism and related phenotypes.

Molecular phenotype and bleeding risks of an inherited platelet disorder in a family with a RUNX1 frameshift mutation.

INTRODUCTION: Inherited defects in RUNX1 are important causes of platelet function disorders. AIM: Our goals were to evaluate RUNX1-related platelet disorders among individuals evaluated for uncharacterized, inherited platelet function disorders and test a proof of concept that bleeding risks could be quantitatively estimated for typical families with an inherited platelet function disorder. METHODS: Index cases with an uncharacterized inherited platelet function disorder were subjected to exome sequencing with confirmation of RUNX1 mutations by Sanger sequencing. Laboratory findings were obtained from medical records and persistence of platelet non-muscle myosin heavy chain IIB (MYH10), a biomarker of RUNX1 defects, was assessed by Western blotting. Bleeding histories were assessed using standardized assessment tools. Bleeding risks were estimated as odds ratios (OR) using questionnaire data for affected individuals compared to controls. RESULTS: Among 12 index cases who had their exomes sequenced, one individual from a family with eight study participants had a c.583dup in RUNX1 that segregated with the disease and was predicted to cause a frameshift and RUNX1 haploinsufficiency. Unlike unaffected family members (n = 2), affected family members (n = 6) had increased bleeding scores and abnormal platelet aggregation and dense granule release responses to agonists but only some had thrombocytopenia and/or dense granule deficiency. This family's mutation was associated with persistence of MYH10 in platelets and increased risks (OR 11-440) for wound healing problems and mild bleeding symptoms, including bleeding interfering with lifestyle in women. CONCLUSION: Inherited platelet dysfunction due to a RUNX1 haploinsufficiency mutation significantly increases bleeding risks.

Genomic approaches to bleeding disorders.

The genes encoding the coagulation factors were characterized over two decades ago. Since then, significant progress has been made in the genetic diagnosis of the two commonest severe inherited bleeding disorders, haemophilia A and B. Experience with the genetic of inherited rare bleeding disorders and platelet disorders is less well advanced. Rare bleeding disorders are usually inherited as autosomal recessive disorders, while it is now clear that a number of the more common platelet function disorders are inherited as autosomal dominant traits. In both cases, DNA sequencing has been useful since most of these disorders are due to mutations located at the coding regions or splice sites of genes encoding the abnormal protein. However, in 5-10% of patients affected with severe clotting factor deficiencies, no genetic defect can be identified and until recently, the genetic characterization of inherited platelet disorders had been confined to the more prevalent conditions such as Glanzmann disease and Bernard-Soulier syndrome. In patients with no gene mutations identified, so far, the role of next-generation sequencing as well as of other new genomic technologies will very likely have increasing importance. However, such methods require extensive bioinformatics analysis that, in turn will require critical revision of our current diagnostic infrastructure.

Regional heritability mapping method helps explain missing heritability of blood lipid traits in isolated populations.

Single single-nucleotide polymorphism (SNP) genome-wide association studies (SSGWAS) may fail to identify loci with modest effects on a trait. The recently developed regional heritability mapping (RHM) method can potentially identify such loci. In this study, RHM was compared with the SSGWAS for blood lipid traits (high-density lipoprotein (HDL), low-density lipoprotein (LDL), plasma concentrations of total cholesterol (TC) and triglycerides (TG)). Data comprised 2246 adults from isolated populations genotyped using ∼300 000 SNP arrays. The results were compared with large meta-analyses of these traits for validation. Using RHM, two significant regions affecting HDL on chromosomes 15 and 16 and one affecting LDL on chromosome 19 were identified. These regions covered the most significant SNPs associated with HDL and LDL from the meta-analysis. The chromosome 19 region was identified in our data despite the fact that the most significant SNP in the meta-analysis (or any SNP tagging it) was not genotyped in our SNP array. The SSGWAS identified one SNP associated with HDL on chromosome 16 (the top meta-analysis SNP) and one on chromosome 10 (not reported by RHM or in the meta-analysis and hence possibly a false positive association). The results further confirm that RHM can have better power than SSGWAS in detecting causal regions including regions containing crucial ungenotyped variants. This study suggests that RHM can be a useful tool to explain some of the 'missing heritability' of complex trait variation.

Potential role of coenzyme Q10 in facilitating recovery from statin-induced rhabdomyolysis.

Rhabdomyolysis is a rare, but serious complication of statin therapy, and represents the most severe end of the spectrum of statin-induced myotoxicity. We report a case where coenzyme Q10 facilitated recovery from statin-induced rhabdomyolysis and acute renal failure, which had initially persisted despite statin cessation and haemodialysis. This observation is biologically plausible due to the recognised importance of coenzyme Q10 in mitochondrial bioenergetics within myocytes, and the fact that statins inhibit farnesyl pyrophosphate production, a biochemical step crucial for coenzyme Q10 synthesis. Coenzyme Q10 is generally well tolerated, and may potentially benefit patients with statin-induced rhabdomyolysis.

A K(ATP) channel gene effect on sleep duration: from genome-wide association studies to function in Drosophila.

Humans sleep approximately a third of their lifetime. The observation that individuals with either long or short sleep duration show associations with metabolic syndrome and psychiatric disorders suggests that the length of sleep is adaptive. Although sleep duration can be influenced by photoperiod (season) and phase of entrainment (chronotype), human familial sleep disorders indicate that there is a strong genetic modulation of sleep. Therefore, we conducted high-density genome-wide association studies for sleep duration in seven European populations (N=4251). We identified an intronic variant (rs11046205; P=3.99 × 10(-8)) in the ABCC9 gene that explains ≈5% of the variation in sleep duration. An influence of season and chronotype on sleep duration was solely observed in the replication sample (N=5949). Meta-analysis of the associations found in a subgroup of the replication sample, chosen for season of entry and chronotype, together with the discovery results showed genome-wide significance. RNA interference knockdown experiments of the conserved ABCC9 homologue in Drosophila neurons renders flies sleepless during the first 3 h of the night. ABCC9 encodes an ATP-sensitive potassium channel subunit (SUR2), serving as a sensor of intracellular energy metabolism.

Fetally-encoded GDF15 and maternal GDF15 sensitivity are major determinants of nausea and vomiting in human pregnancy.

Human pregnancy is frequently accompanied by nausea and vomiting that may become severe and life-threatening, as in hyperemesis gravidarum (HG), the cause of which is unknown. Growth Differentiation Factor-15 (GDF15), a hormone known to act on the hindbrain to cause emesis, is highly expressed in the placenta and its levels in maternal blood rise rapidly in pregnancy. Variants in the maternal GDF15 gene are associated with HG. Here we report that fetal production of GDF15, and maternal sensitivity to it, both contribute substantially to the risk of HG. We found that the great majority of GDF15 in maternal circulation is derived from the feto-placental unit and that higher GDF15 levels in maternal blood are associated with vomiting and are further elevated in patients with HG. Conversely, we found that lower levels of GDF15 in the non-pregnant state predispose women to HG. A rare C211G variant in GDF15 which strongly predisposes mothers to HG, particularly when the fetus is wild-type, was found to markedly impair cellular secretion of GDF15 and associate with low circulating levels of GDF15 in the non-pregnant state. Consistent with this, two common GDF15 haplotypes which predispose to HG were associated with lower circulating levels outside pregnancy. The administration of a long-acting form of GDF15 to wild-type mice markedly reduced subsequent responses to an acute dose, establishing that desensitisation is a feature of this system. GDF15 levels are known to be highly and chronically elevated in patients with beta thalassemia. In women with this disorder, reports of symptoms of nausea or vomiting in pregnancy were strikingly diminished. Our findings support a causal role for fetal derived GDF15 in the nausea and vomiting of human pregnancy, with maternal sensitivity, at least partly determined by pre-pregnancy exposure to GDF15, being a major influence on its severity. They also suggest mechanism-based approaches to the treatment and prevention of HG.

SNP mistyping in genotyping arrays--an important cause of spurious association in case-control studies.

Using genome-wide association studies to identify genetic variants contributing to disease has been highly successful with many novel genetic predispositions identified and biological pathways revealed. Several pitfalls for spurious association or non-replication have been highlighted: from population structure, automated genotype scoring for cases and controls, to age-varying association. We describe an important yet unreported source of bias in case-control studies due to variations in chip technology between different commercial array releases. As cases are commonly genotyped with newer arrays and freely available control resources are frequently used for comparison, there exists an important potential for false associations which are robust to standard quality control and replication design.

Global haemostasis and point of care testing.

The evaluation of the coagulation profile has used so far either clotting-based or chromogenic assays with different endpoints. Clotting-based techniques are the most used worldwide, and they certainly are useful for diagnosis of clotting factor deficiencies. However, the information provided is relatively limited, and therefore the individual profile of coagulation is poorly assessed. This is reflected by the weak correlation between the results of these assays and the clinical phenotype. Among the assays that benefited from technological advances, thrombin generation and thromboelastography are probably the most actively investigated, but they require specific instruments and are not fully automated. Their standardisation level is rapidly progressing, and they are progressively entering the clinical scene, with the attempt to provide additional information on the coagulation process and a meaningful clinical correlation. These inherited bleeding disorders frequently require replacement therapy using clotting factor concentrates that increase the plasma level of the missing clotting factor. The classical adjustment of the therapy is mainly based on the measurement of the plasma clotting activity of the protein administered. If one considers that a certain level of thrombin generated would predict clinical efficacy, monitoring of thrombin formation might offer new possibilities to individually predict the bleeding phenotype, select the most adapted therapeutic product and tailor the dose. The same holds true for thromboelastography/thromboelastometry which evaluate fibrin formation as well as clot resistance to fibrinolytic challenge, one step further down in the coagulation process. In this regard, these 2 assays could be seen as complementary in terms of information provided on the coagulation profile at the individual level.