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author:("Palotie, arno")
1.  Genome-wide association and longitudinal analyses reveal genetic loci linking pubertal height growth, pubertal timing and childhood adiposity 
Human Molecular Genetics  2013;22(13):2735-2747.
The pubertal height growth spurt is a distinctive feature of childhood growth reflecting both the central onset of puberty and local growth factors. Although little is known about the underlying genetics, growth variability during puberty correlates with adult risks for hormone-dependent cancer and adverse cardiometabolic health. The only gene so far associated with pubertal height growth, LIN28B, pleiotropically influences childhood growth, puberty and cancer progression, pointing to shared underlying mechanisms. To discover genetic loci influencing pubertal height and growth and to place them in context of overall growth and maturation, we performed genome-wide association meta-analyses in 18 737 European samples utilizing longitudinally collected height measurements. We found significant associations (P < 1.67 × 10−8) at 10 loci, including LIN28B. Five loci associated with pubertal timing, all impacting multiple aspects of growth. In particular, a novel variant correlated with expression of MAPK3, and associated both with increased prepubertal growth and earlier menarche. Another variant near ADCY3-POMC associated with increased body mass index, reduced pubertal growth and earlier puberty. Whereas epidemiological correlations suggest that early puberty marks a pathway from rapid prepubertal growth to reduced final height and adult obesity, our study shows that individual loci associating with pubertal growth have variable longitudinal growth patterns that may differ from epidemiological observations. Overall, this study uncovers part of the complex genetic architecture linking pubertal height growth, the timing of puberty and childhood obesity and provides new information to pinpoint processes linking these traits.
doi:10.1093/hmg/ddt104
PMCID: PMC3674797  PMID: 23449627
2.  A balanced translocation truncates Neurotrimin in a family with intracranial and thoracic aortic aneurysm 
Journal of medical genetics  2012;49(10):621-629.
Background
Balanced chromosomal rearrangements occasionally have strong phenotypic effects, which may be useful in understanding pathobiology. However, conventional strategies for characterizing breakpoints are laborious and inaccurate. We present here a proband with a thoracic aortic aneurysm and a balanced translocation t(10;11)(q23.2;q24.2). Our purpose was to sequence the chromosomal breaks in this family to reveal a novel candidate gene for aneurysm.
Methods and results
Intracranial and thoracic aortic aneurysms appear to run in the family in an autosomal dominant manner: After exploring the family history, we observed that the proband’s two siblings both died from cerebral hemorrhage, and the proband’s parent and parent’s sibling died from aortic rupture. After application of a genome-wide paired-end DNA sequencing method for breakpoint mapping, we demonstrate that this translocation breaks intron 1 of a splicing isoform of Neurotrimin (NTM) at 11q25 in a previously implicated candidate region for intracranial (IAs) and aortic aneurysms (AAs) (OMIM 612161).
Conclusions
Our results demonstrate the feasibility of genome-wide paired-end sequencing for the characterization of balanced rearrangements and identification of candidate genes in patients with potentially disease-associated chromosome rearrangements. The family samples were gathered as a part of our recently launched National Registry of Reciprocal Balanced Translocations and Inversions in Finland (n=2575), and we believe that such a registry will be a powerful resource for the localization of chromosomal aberrations, which can bring insight into the etiology of related phenotypes.
doi:10.1136/jmedgenet-2012-100977
PMCID: PMC4039200  PMID: 23054244
Molecular genetics; Cardiovascular Medicine; Chromosomal; Clinical Genetics; Genome-wide
3.  A genetic study of Wilson’s disease in the United Kingdom 
Brain  2013;136(5):1476-1487.
Previous studies have failed to identify mutations in the Wilson’s disease gene ATP7B in a significant number of clinically diagnosed cases. This has led to concerns about genetic heterogeneity for this condition but also suggested the presence of unusual mutational mechanisms. We now present our findings in 181 patients from the United Kingdom with clinically and biochemically confirmed Wilson’s disease. A total of 116 different ATP7B mutations were detected, 32 of which are novel. The overall mutation detection frequency was 98%. The likelihood of mutations in genes other than ATP7B causing a Wilson’s disease phenotype is therefore very low. We report the first cases with Wilson’s disease due to segmental uniparental isodisomy as well as three patients with three ATP7B mutations and three families with Wilson’s disease in two consecutive generations. We determined the genetic prevalence of Wilson’s disease in the United Kingdom by sequencing the entire coding region and adjacent splice sites of ATP7B in 1000 control subjects. The frequency of all single nucleotide variants with in silico evidence of pathogenicity (Class 1 variant) was 0.056 or 0.040 if only those single nucleotide variants that had previously been reported as mutations in patients with Wilson’s disease were included in the analysis (Class 2 variant). The frequency of heterozygote, putative or definite disease-associated ATP7B mutations was therefore considerably higher than the previously reported occurrence of 1:90 (or 0.011) for heterozygote ATP7B mutation carriers in the general population (P < 2.2 × 10-16 for Class 1 variants or P < 5 × 10-11 for Class 2 variants only). Subsequent exclusion of four Class 2 variants without additional in silico evidence of pathogenicity led to a further reduction of the mutation frequency to 0.024. Using this most conservative approach, the calculated frequency of individuals predicted to carry two mutant pathogenic ATP7B alleles is 1:7026 and thus still considerably higher than the typically reported prevalence of Wilson’s disease of 1:30 000 (P = 0.00093). Our study provides strong evidence for monogenic inheritance of Wilson’s disease. It also has major implications for ATP7B analysis in clinical practice, namely the need to consider unusual genetic mechanisms such as uniparental disomy or the possible presence of three ATP7B mutations. The marked discrepancy between the genetic prevalence and the number of clinically diagnosed cases of Wilson’s disease may be due to both reduced penetrance of ATP7B mutations and failure to diagnose patients with this eminently treatable disorder.
doi:10.1093/brain/awt035
PMCID: PMC3634195  PMID: 23518715
Wilson’s disease; ATP7B; genetic prevalence
4.  Deletion of TOP3β, a component of FMRP-containing mRNPs, contributes to neurodevelopmental disorders 
Nature neuroscience  2013;16(9):1228-1237.
Implicating particular genes in the generation of complex brain and behavior phenotypes requires multiple lines of evidence. The rarity of most high impact genetic variants typically precludes the possibility of accruing statistical evidence that they are associated with a given trait. We show here that the enrichment of a rare Chromosome 22q11.22 deletion in a recently expanded Northern Finnish sub-isolate enables the detection of association between TOP3β and both schizophrenia and cognitive impairment. Biochemical analysis of TOP3β revealed that this topoisomerase is a component of cytosolic messenger ribonucleoproteins (mRNPs) and is catalytically active on RNA. The recruitment of TOP3β to mRNPs was independent of RNA cis-elements and was coupled to the co-recruitment of FMRP, the disease gene product in fragile X mental retardation syndrome (FXS). Thus, we uncover a novel role for TOP3β in mRNA metabolism and provide several lines of evidence implicating it in neurodevelopmental disorders.
doi:10.1038/nn.3484
PMCID: PMC3986889  PMID: 23912948
5.  A Central Role for GRB10 in Regulation of Islet Function in Man 
PLoS Genetics  2014;10(4):e1004235.
Variants in the growth factor receptor-bound protein 10 (GRB10) gene were in a GWAS meta-analysis associated with reduced glucose-stimulated insulin secretion and increased risk of type 2 diabetes (T2D) if inherited from the father, but inexplicably reduced fasting glucose when inherited from the mother. GRB10 is a negative regulator of insulin signaling and imprinted in a parent-of-origin fashion in different tissues. GRB10 knock-down in human pancreatic islets showed reduced insulin and glucagon secretion, which together with changes in insulin sensitivity may explain the paradoxical reduction of glucose despite a decrease in insulin secretion. Together, these findings suggest that tissue-specific methylation and possibly imprinting of GRB10 can influence glucose metabolism and contribute to T2D pathogenesis. The data also emphasize the need in genetic studies to consider whether risk alleles are inherited from the mother or the father.
Author Summary
In this paper, we report the first large genome-wide association study in man for glucose-stimulated insulin secretion (GSIS) indices during an oral glucose tolerance test. We identify seven genetic loci and provide effects on GSIS for all previously reported glycemic traits and obesity genetic loci in a large-scale sample. We observe paradoxical effects of genetic variants in the growth factor receptor-bound protein 10 (GRB10) gene yielding both reduced GSIS and reduced fasting plasma glucose concentrations, specifically showing a parent-of-origin effect of GRB10 on lower fasting plasma glucose and enhanced insulin sensitivity for maternal and elevated glucose and decreased insulin sensitivity for paternal transmissions of the risk allele. We also observe tissue-specific differences in DNA methylation and allelic imbalance in expression of GRB10 in human pancreatic islets. We further disrupt GRB10 by shRNA in human islets, showing reduction of both insulin and glucagon expression and secretion. In conclusion, we provide evidence for complex regulation of GRB10 in human islets. Our data suggest that tissue-specific methylation and imprinting of GRB10 can influence glucose metabolism and contribute to T2D pathogenesis. The data also emphasize the need in genetic studies to consider whether risk alleles are inherited from the mother or the father.
doi:10.1371/journal.pgen.1004235
PMCID: PMC3974640  PMID: 24699409
6.  Biomarker Profiling by Nuclear Magnetic Resonance Spectroscopy for the Prediction of All-Cause Mortality: An Observational Study of 17,345 Persons 
PLoS Medicine  2014;11(2):e1001606.
In this study, Würtz and colleagues conducted high-throughput profiling of blood specimens in two large population-based cohorts in order to identify biomarkers for all-cause mortality and enhance risk prediction. The authors found that biomarker profiling improved prediction of the short-term risk of death from all causes above established risk factors. However, further investigations are needed to clarify the biological mechanisms and the utility of these biomarkers to guide screening and prevention.
Please see later in the article for the Editors' Summary
Background
Early identification of ambulatory persons at high short-term risk of death could benefit targeted prevention. To identify biomarkers for all-cause mortality and enhance risk prediction, we conducted high-throughput profiling of blood specimens in two large population-based cohorts.
Methods and Findings
106 candidate biomarkers were quantified by nuclear magnetic resonance spectroscopy of non-fasting plasma samples from a random subset of the Estonian Biobank (n = 9,842; age range 18–103 y; 508 deaths during a median of 5.4 y of follow-up). Biomarkers for all-cause mortality were examined using stepwise proportional hazards models. Significant biomarkers were validated and incremental predictive utility assessed in a population-based cohort from Finland (n = 7,503; 176 deaths during 5 y of follow-up). Four circulating biomarkers predicted the risk of all-cause mortality among participants from the Estonian Biobank after adjusting for conventional risk factors: alpha-1-acid glycoprotein (hazard ratio [HR] 1.67 per 1–standard deviation increment, 95% CI 1.53–1.82, p = 5×10−31), albumin (HR 0.70, 95% CI 0.65–0.76, p = 2×10−18), very-low-density lipoprotein particle size (HR 0.69, 95% CI 0.62–0.77, p = 3×10−12), and citrate (HR 1.33, 95% CI 1.21–1.45, p = 5×10−10). All four biomarkers were predictive of cardiovascular mortality, as well as death from cancer and other nonvascular diseases. One in five participants in the Estonian Biobank cohort with a biomarker summary score within the highest percentile died during the first year of follow-up, indicating prominent systemic reflections of frailty. The biomarker associations all replicated in the Finnish validation cohort. Including the four biomarkers in a risk prediction score improved risk assessment for 5-y mortality (increase in C-statistics 0.031, p = 0.01; continuous reclassification improvement 26.3%, p = 0.001).
Conclusions
Biomarker associations with cardiovascular, nonvascular, and cancer mortality suggest novel systemic connectivities across seemingly disparate morbidities. The biomarker profiling improved prediction of the short-term risk of death from all causes above established risk factors. Further investigations are needed to clarify the biological mechanisms and the utility of these biomarkers for guiding screening and prevention.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
A biomarker is a biological molecule found in blood, body fluids, or tissues that may signal an abnormal process, a condition, or a disease. The level of a particular biomarker may indicate a patient's risk of disease, or likely response to a treatment. For example, cholesterol levels are measured to assess the risk of heart disease. Most current biomarkers are used to test an individual's risk of developing a specific condition. There are none that accurately assess whether a person is at risk of ill health generally, or likely to die soon from a disease. Early and accurate identification of people who appear healthy but in fact have an underlying serious illness would provide valuable opportunities for preventative treatment.
While most tests measure the levels of a specific biomarker, there are some technologies that allow blood samples to be screened for a wide range of biomarkers. These include nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry. These tools have the potential to be used to screen the general population for a range of different biomarkers.
Why Was This Study Done?
Identifying new biomarkers that provide insight into the risk of death from all causes could be an important step in linking different diseases and assessing patient risk. The authors in this study screened patient samples using NMR spectroscopy for biomarkers that accurately predict the risk of death particularly amongst the general population, rather than amongst people already known to be ill.
What Did the Researchers Do and Find?
The researchers studied two large groups of people, one in Estonia and one in Finland. Both countries have set up health registries that collect and store blood samples and health records over many years. The registries include large numbers of people who are representative of the wider population.
The researchers first tested blood samples from a representative subset of the Estonian group, testing 9,842 samples in total. They looked at 106 different biomarkers in each sample using NMR spectroscopy. They also looked at the health records of this group and found that 508 people died during the follow-up period after the blood sample was taken, the majority from heart disease, cancer, and other diseases. Using statistical analysis, they looked for any links between the levels of different biomarkers in the blood and people's short-term risk of dying. They found that the levels of four biomarkers—plasma albumin, alpha-1-acid glycoprotein, very-low-density lipoprotein (VLDL) particle size, and citrate—appeared to accurately predict short-term risk of death. They repeated this study with the Finnish group, this time with 7,503 individuals (176 of whom died during the five-year follow-up period after giving a blood sample) and found similar results.
The researchers carried out further statistical analyses to take into account other known factors that might have contributed to the risk of life-threatening illness. These included factors such as age, weight, tobacco and alcohol use, cholesterol levels, and pre-existing illness, such as diabetes and cancer. The association between the four biomarkers and short-term risk of death remained the same even when controlling for these other factors.
The analysis also showed that combining the test results for all four biomarkers, to produce a biomarker score, provided a more accurate measure of risk than any of the biomarkers individually. This biomarker score also proved to be the strongest predictor of short-term risk of dying in the Estonian group. Individuals with a biomarker score in the top 20% had a risk of dying within five years that was 19 times greater than that of individuals with a score in the bottom 20% (288 versus 15 deaths).
What Do These Findings Mean?
This study suggests that there are four biomarkers in the blood—alpha-1-acid glycoprotein, albumin, VLDL particle size, and citrate—that can be measured by NMR spectroscopy to assess whether otherwise healthy people are at short-term risk of dying from heart disease, cancer, and other illnesses. However, further validation of these findings is still required, and additional studies should examine the biomarker specificity and associations in settings closer to clinical practice. The combined biomarker score appears to be a more accurate predictor of risk than tests for more commonly known risk factors. Identifying individuals who are at high risk using these biomarkers might help to target preventative medical treatments to those with the greatest need.
However, there are several limitations to this study. As an observational study, it provides evidence of only a correlation between a biomarker score and ill health. It does not identify any underlying causes. Other factors, not detectable by NMR spectroscopy, might be the true cause of serious health problems and would provide a more accurate assessment of risk. Nor does this study identify what kinds of treatment might prove successful in reducing the risks. Therefore, more research is needed to determine whether testing for these biomarkers would provide any clinical benefit.
There were also some technical limitations to the study. NMR spectroscopy does not detect as many biomarkers as mass spectrometry, which might therefore identify further biomarkers for a more accurate risk assessment. In addition, because both study groups were northern European, it is not yet known whether the results would be the same in other ethnic groups or populations with different lifestyles.
In spite of these limitations, the fact that the same four biomarkers are associated with a short-term risk of death from a variety of diseases does suggest that similar underlying mechanisms are taking place. This observation points to some potentially valuable areas of research to understand precisely what's contributing to the increased risk.
Additional Information
Please access these websites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001606
The US National Institute of Environmental Health Sciences has information on biomarkers
The US Food and Drug Administration has a Biomarker Qualification Program to help researchers in identifying and evaluating new biomarkers
Further information on the Estonian Biobank is available
The Computational Medicine Research Team of the University of Oulu and the University of Bristol have a webpage that provides further information on high-throughput biomarker profiling by NMR spectroscopy
doi:10.1371/journal.pmed.1001606
PMCID: PMC3934819  PMID: 24586121
7.  High Risk Population Isolate Reveals Low Frequency Variants Predisposing to Intracranial Aneurysms 
PLoS Genetics  2014;10(1):e1004134.
3% of the population develops saccular intracranial aneurysms (sIAs), a complex trait, with a sporadic and a familial form. Subarachnoid hemorrhage from sIA (sIA-SAH) is a devastating form of stroke. Certain rare genetic variants are enriched in the Finns, a population isolate with a small founder population and bottleneck events. As the sIA-SAH incidence in Finland is >2× increased, such variants may associate with sIA in the Finnish population. We tested 9.4 million variants for association in 760 Finnish sIA patients (enriched for familial sIA), and in 2,513 matched controls with case-control status and with the number of sIAs. The most promising loci (p<5E-6) were replicated in 858 Finnish sIA patients and 4,048 controls. The frequencies and effect sizes of the replicated variants were compared to a continental European population using 717 Dutch cases and 3,004 controls. We discovered four new high-risk loci with low frequency lead variants. Three were associated with the case-control status: 2q23.3 (MAF 2.1%, OR 1.89, p 1.42×10-9); 5q31.3 (MAF 2.7%, OR 1.66, p 3.17×10-8); 6q24.2 (MAF 2.6%, OR 1.87, p 1.87×10-11) and one with the number of sIAs: 7p22.1 (MAF 3.3%, RR 1.59, p 6.08×-9). Two of the associations (5q31.3, 6q24.2) replicated in the Dutch sample. The 7p22.1 locus was strongly differentiated; the lead variant was more frequent in Finland (4.6%) than in the Netherlands (0.3%). Additionally, we replicated a previously inconclusive locus on 2q33.1 in all samples tested (OR 1.27, p 1.87×10-12). The five loci explain 2.1% of the sIA heritability in Finland, and may relate to, but not explain, the increased incidence of sIA-SAH in Finland. This study illustrates the utility of population isolates, familial enrichment, dense genotype imputation and alternate phenotyping in search for variants associated with complex diseases.
Author Summary
Genome-wide association studies (GWAS) have been extensively used to identify common genetic variants associated with complex diseases. As common genetic variants have explained only a small fraction of the heritability of most complex diseases, there is a growing interest in the role of how low frequency and rare variants contribute to the susceptibility. Low frequency variants are more often specific to populations of distinct ancestries. Saccular intracranial aneurysms (sIA) are balloon-like dilatations in the arteries on the surface of the brain. The rupture of sIA causes life-threatening intracranial bleeding. sIA is a complex disease, which is known to sometimes run in families. Here, we utilize the recent advancements in knowledge of genetic variation in different populations to examine the role of low-frequency variants in sIA disease in the isolated population of Finland where sIA related strokes are more common than in most other populations. By studying >8000 Finns we identify four low-frequency variants associated with the sIA disease. We also show that the association of two of the variants are seen in other European populations as well. Our findings demonstrate that multiple study designs are needed to uncover more comprehensively their genetic background, including population isolates.
doi:10.1371/journal.pgen.1004134
PMCID: PMC3907358  PMID: 24497844
8.  Maintenance of genetic variation in human personality: Testing evolutionary models by estimating heritability due to common causal variants and investigating the effect of distant inbreeding 
Personality traits are basic dimensions of behavioural variation, and twin, family, and adoption studies show that around 30% of the between-individual variation is due to genetic variation. There is rapidly-growing interest in understanding the evolutionary basis of this genetic variation. Several evolutionary mechanisms could explain how genetic variation is maintained in traits, and each of these makes predictions in terms of the relative contribution of rare and common genetic variants to personality variation, the magnitude of nonadditive genetic influences, and whether personality is affected by inbreeding. Using genome-wide SNP data from >8,000 individuals, we estimated that little variation in the Cloninger personality dimensions (7.2% on average) is due to the combined effect of common, additive genetic variants across the genome, suggesting that most heritable variation in personality is due to rare variant effects and/or a combination of dominance and epistasis. Furthermore, higher levels of inbreeding were associated with less socially-desirable personality trait levels in three of the four personality dimensions. These findings are consistent with genetic variation in personality traits having been maintained by mutation-selection balance.
doi:10.1111/j.1558-5646.2012.01679.x
PMCID: PMC3518920  PMID: 23025612
balancing selection; mutation-selection balance; antagonistic pleiotropy; correlational selection; neutral; trade-offs; personality; temperament; mutation; evolution; behavioural syndromes
9.  Meta-analysis of genome-wide association studies for personality 
Molecular psychiatry  2010;17(3):337-349.
Personality can be thought of as a set of characteristics that influence people’s thoughts, feelings, and behaviour across a variety of settings. Variation in personality is predictive of many outcomes in life, including mental health. Here we report on a meta-analysis of genome-wide association (GWA) data for personality in ten discovery samples (17 375 adults) and five in-silico replication samples (3 294 adults). All participants were of European ancestry. Personality scores for Neuroticism, Extraversion, Openness to Experience, Agreeableness, and Conscientiousness were based on the NEO Five-Factor Inventory. Genotype data were available of ~2.4M Single Nucleotide Polymorphisms (SNPs; directly typed and imputed using HAPMAP data). In the discovery samples, classical association analyses were performed under an additive model followed by meta-analysis using the weighted inverse variance method. Results showed genome-wide significance for Openness to Experience near the RASA1 gene on 5q14.3 (rs1477268 and rs2032794, P = 2.8 × 10−8 and 3.1 × 10−8) and for Conscientiousness in the brain-expressed KATNAL2 gene on 18q21.1 (rs2576037, P = 4.9 × 10−8). We further conducted a gene-based test that confirmed the association of KATNAL2 to Conscientiousness. In-silico replication did not, however, show significant associations of the top SNPs with Openness and Conscientiousness, although the direction of effect of the KATNAL2 SNP on Conscientiousness was consistent in all replication samples. Larger scale GWA studies and alternative approaches are required for confirmation of KATNAL2 as a novel gene affecting Conscientiousness.
doi:10.1038/mp.2010.128
PMCID: PMC3785122  PMID: 21173776
Personality; Five-Factor Model; Genome-wide association; Meta-analysis; Genetic variants
10.  Common Variants on 8p12 and 1q24.2 Confer Risk of Schizophrenia 
Nature genetics  2011;43(12):1224-1227.
Schizophrenia is a severe mental disorder affecting ~1% of the world population, with heritability of up to 80%. To identify new common genetic risk factors, we performed a genome-wide association study (GWAS) in the Han Chinese population. The discovery sample set consisted of 3,750 patients and 6,468 healthy controls (1,578 cases and 1,592 controls from the Northern Han; 1,238 cases and 2,856 controls from the Central Han; 934 cases and 2,020 controls from the Southern Han); and we followed up the top association signals in an additional independent cohort of 4,383 cases and 4,539 controls from the Han Chinese. Meta-analysis identified genome-wide significant association of common SNPs with schizophrenia on chromosome 8p12 (rs16887244, P=1.27×10−10) and 1q24.2 (rs10489202, P=9.50×10−9). Our findings provide new insights into the pathogenesis of schizophrenia.
doi:10.1038/ng.980
PMCID: PMC3773910  PMID: 22037555
11.  Genome-wide association analysis identifies susceptibility loci for migraine without aura 
Nature genetics  2012;44(7):777-782.
Migraine without aura is the most common form of migraine, characterized by recurrent disabling headache and associated autonomic symptoms. To identify common genetic variants for this migraine type, we analyzed genome-wide association data of 2,326 clinic-based German and Dutch patients and 4,580 population-matched controls. We selected SNPs from 12 loci with two or more SNPs with P-values < 1 × 10−5 for follow-up in 2,508 patients and 2,652 controls. Two loci, i.e. 1q22 (MEF2D) and 3p24 (near TGFBR2) replicated convincingly (P = 4.9 × 10−4, P = 1.0 × 10−4, respectively). Meta-analysis of the discovery and replication data yielded two additional genome-wide significant (P < 5 × 10−8) loci in PHACTR1 and ASTN2. In addition, SNPs in two previously reported migraine loci in or near TRPM8 and LRP1 significantly replicated. This study reveals the first susceptibility loci for migraine without aura, thereby expanding our knowledge of this debilitating neurological disorder.
doi:10.1038/ng.2307
PMCID: PMC3773912  PMID: 22683712
12.  Novel mutations consolidate KCTD7 as a progressive myoclonus epilepsy gene 
Journal of medical genetics  2012;49(6):391-399.
Background
The progressive myoclonus epilepsies (PMEs) comprise a group of clinically and genetically heterogeneous disorders characterized by myoclonus, epilepsy, and neurological deterioration. We aimed to identify the underlying gene(s) in childhood-onset PME patients with unknown molecular genetic background.
Methods
Homozygosity mapping was applied on genome-wide SNP data of 18 Turkish patients. The potassium channel tetramerization domain-containing 7 (KCTD7) gene, previously associated with PME in a single inbred family, was screened for mutations. The spatiotemporal expression of KCTD7 was assessed in cellular cultures and mouse brain tissue.
Results
Overlapping homozygosity in 8/18 patients defined a 1.5 Mb segment on 7q11.21 as the major candidate locus. Screening of the positional candidate gene KCTD7 revealed homozygous missense mutations in two of the eight cases. Screening of KCTD7 in further 132 PME patients revealed four additional mutations (two missense, one in-frame deletion and one frameshift-causing) in five families. Eight patients presented with myoclonus and epilepsy and one with ataxia, the mean age of onset being 19 months. Within two years after onset progressive loss of mental and motor skills ensued leading to severe dementia and motor handicap. KCTD7 showed cytosolic localization and predominant neuronal expression, with widespread expression throughout the brain. None of three polypeptides carrying patient missense mutations affected the subcellular distribution of KCTD7.
Discussion
Our data confirm the causality of KCTD7 defects in PME, and imply that KCTD7 mutation screening should be considered in PME patients with onset around 2 years of age followed by rapid mental and motor deterioration.
doi:10.1136/jmedgenet-2012-100859
PMCID: PMC3773914  PMID: 22693283
myoclonus; mutation; neurodegenerative disorders; mental retardation; pediatric epilepsy
14.  Pubertal Timing and Growth Influences Cardiometabolic Risk Factors in Adult Males and Females 
Diabetes Care  2012;35(4):850-856.
OBJECTIVE
Early pubertal onset in females is associated with increased risk for adult obesity and cardiovascular disease, but whether this relationship is independent of preceding childhood growth events is unclear. Furthermore, the association between male puberty and adult disease remains unknown. To clarify the link between puberty and adult health, we evaluated the relationship between pubertal timing and risk factors for type 2 diabetes and cardiovascular disease in both males and females from a large, prospective, and randomly ascertained birth cohort from Northern Finland.
RESEARCH DESIGN AND METHODS
Pubertal timing was estimated based on pubertal height growth in 5,058 subjects (2,417 males and 2,641 females), and the relationship between puberty and body weight, glucose and lipid homeostasis, and blood pressure at age 31 years was evaluated with linear regression modeling.
RESULTS
Earlier pubertal timing associated with higher adult BMI, fasting insulin, diastolic blood pressure, and decreased HDL cholesterol in both sexes (P < 0.002) and with higher total serum cholesterol, LDL cholesterol, and triglycerides in males. The association with BMI and diastolic blood pressure remained statistically significant in both sexes, as did the association with insulin levels and HDL cholesterol concentrations in males after adjusting for covariates reflecting both fetal and childhood growth including childhood BMI.
CONCLUSIONS
We demonstrate independent association between earlier pubertal timing and adult metabolic syndrome-related derangements both in males and females. The connection emphasizes that the mechanisms advancing puberty may also contribute to adult metabolic disorders.
doi:10.2337/dc11-1365
PMCID: PMC3308310  PMID: 22338106
15.  From genetic discovery to future personalized health research 
New Biotechnology  2013;30(3):291-295.
During the past ten years the field of human disease genetics has made major leaps, including the completion of the Human Genome Project, the HapMap Project, the development of the genome-wide association (GWA) studies to identify common disease-predisposing variants and the introduction of large-scale whole-genome and whole-exome sequencing studies. The introduction of new technologies has enabled researchers to utilize novel study designs to tackle previously unexplored research questions in human genomics. These new types of studies typically need large sample sizes to overcome the multiple testing challenges caused by the huge number of interrogated genetic variants. As a consequence, large consortia-studies are at present the default in disease genetics research. The systematic planning of the GWA-studies was a key element in the success of the approach. Similar planning and rigor in statistical inferences will probably be beneficial also to future sequencing studies. Already today, the next-generation exome sequencing has led to the identification of several genes underlying Mendelian diseases. In spite of the clear benefits, the method has proven to be more challenging than anticipated. In the case of complex diseases, next-generation sequencing aims to identify disease-associated low-frequency alleles. However, their robust detection will require very large study samples, even larger than in the case of the GWA-studies. This has stimulated study designs that capitalize on enriching sets of low-frequency alleles, for example, studies focusing on population isolates such as Finland or Iceland. One example is the collaborative SISu Project (Sequencing Initiative Suomi) that aims to provide near complete genome variation information from Finnish study samples and pave the way for large, nationwide genome health initiative studies.
doi:10.1016/j.nbt.2012.11.013
PMCID: PMC3627963  PMID: 23165095
16.  Genome-wide association study identifies multiple loci influencing human serum metabolite levels 
Nature genetics  2012;44(3):269-276.
Nuclear magnetic resonance assays allow for measurement of a wide range of metabolic phenotypes. We report here the results of a GWAS on 8,330 Finnish individuals genotyped and imputed at 7.7 million SNPs for a range of 216 serum metabolic phenotypes assessed by NMR of serum samples. We identified significant associations (P < 2.31 × 10−10) at 31 loci, including 11 for which there have not been previous reports of associations to a metabolic trait or disorder. Analyses of Finnish twin pairs suggested that the metabolic measures reported here show higher heritability than comparable conventional metabolic phenotypes. In accordance with our expectations, SNPs at the 31 loci associated with individual metabolites account for a greater proportion of the genetic component of trait variance (up to 40%) than is typically observed for conventional serum metabolic phenotypes. The identification of such associations may provide substantial insight into cardiometabolic disorders.
doi:10.1038/ng.1073
PMCID: PMC3605033  PMID: 22286219
18.  A Potential Novel Spontaneous Preterm Birth Gene, AR, Identified by Linkage and Association Analysis of X Chromosomal Markers 
PLoS ONE  2012;7(12):e51378.
Preterm birth is the major cause of neonatal mortality and morbidity. In many cases, it has severe life-long consequences for the health and neurological development of the newborn child. More than 50% of all preterm births are spontaneous, and currently there is no effective prevention. Several studies suggest that genetic factors play a role in spontaneous preterm birth (SPTB). However, its genetic background is insufficiently characterized. The aim of the present study was to perform a linkage analysis of X chromosomal markers in SPTB in large northern Finnish families with recurrent SPTBs. We found a significant linkage signal (HLOD  = 3.72) on chromosome locus Xq13.1 when the studied phenotype was being born preterm. There were no significant linkage signals when the studied phenotype was giving preterm deliveries. Two functional candidate genes, those encoding the androgen receptor (AR) and the interleukin-2 receptor gamma subunit (IL2RG), located near this locus were analyzed as candidates for SPTB in subsequent case-control association analyses. Nine single-nucleotide polymorphisms (SNPs) within these genes and an AR exon-1 CAG repeat, which was previously demonstrated to be functionally significant, were analyzed in mothers with preterm delivery (n = 272) and their offspring (n = 269), and in mothers with exclusively term deliveries (n = 201) and their offspring (n = 199), all originating from northern Finland. A replication study population consisting of individuals born preterm (n = 111) and term (n = 197) from southern Finland was also analyzed. Long AR CAG repeats (≥26) were overrepresented and short repeats (≤19) underrepresented in individuals born preterm compared to those born at term. Thus, our linkage and association results emphasize the role of the fetal genome in genetic predisposition to SPTB and implicate AR as a potential novel fetal susceptibility gene for SPTB.
doi:10.1371/journal.pone.0051378
PMCID: PMC3515491  PMID: 23227263
19.  A Comparison of the Whole Genome Approach of MeDIP-Seq to the Targeted Approach of the Infinium HumanMethylation450 BeadChip® for Methylome Profiling 
PLoS ONE  2012;7(11):e50233.
DNA methylation is one of the most studied epigenetic marks in the human genome, with the result that the desire to map the human methylome has driven the development of several methods to map DNA methylation on a genomic scale. Our study presents the first comparison of two of these techniques - the targeted approach of the Infinium HumanMethylation450 BeadChip® with the immunoprecipitation and sequencing-based method, MeDIP-seq. Both methods were initially validated with respect to bisulfite sequencing as the gold standard and then assessed in terms of coverage, resolution and accuracy. The regions of the methylome that can be assayed by both methods and those that can only be assayed by one method were determined and the discovery of differentially methylated regions (DMRs) by both techniques was examined. Our results show that the Infinium HumanMethylation450 BeadChip® and MeDIP-seq show a good positive correlation (Spearman correlation of 0.68) on a genome-wide scale and can both be used successfully to determine differentially methylated loci in RefSeq genes, CpG islands, shores and shelves. MeDIP-seq however, allows a wider interrogation of methylated regions of the human genome, including thousands of non-RefSeq genes and repetitive elements, all of which may be of importance in disease. In our study MeDIP-seq allowed the detection of 15,709 differentially methylated regions, nearly twice as many as the array-based method (8070), which may result in a more comprehensive study of the methylome.
doi:10.1371/journal.pone.0050233
PMCID: PMC3510246  PMID: 23209683
20.  Identification of quantitative trait loci for fibrin clot phenotypes: The EuroCLOT study 
Objectives
Fibrin makes up the structural basis of an occlusive arterial thrombus and variability in fibrin phenotype relates to cardiovascular risk. The aims of the current study from the EU consortium EuroCLOT were to 1) determine the heritability of fibrin phenotypes and 2) identify QTLs associated with fibrin phenotypes.
Methods
447 dizygotic (DZ) and 460 monozygotic (MZ) pairs of healthy UK Caucasian female twins and 199 DZ twin pairs from Denmark were studied. D-dimer, an indicator of fibrin turnover, was measured by ELISA and measures of clot formation, morphology and lysis were determined by turbidimetric assays. Heritability estimates and genome-wide linkage analysis were performed.
Results
Estimates of heritability for d-dimer and turbidometric variables were in the range 17 - 46%, with highest levels for maximal absorbance which provides an estimate of clot density. Genome-wide linkage analysis revealed 6 significant regions with LOD>3 on 5 chromosomes (5, 6, 9, 16 and 17).
Conclusions
The results indicate a significant genetic contribution to variability in fibrin phenotypes and highlight regions in the human genome which warrant further investigation in relation to ischaemic cardiovascular disorders and their therapy.
doi:10.1161/ATVBAHA.108.178103
PMCID: PMC3508477  PMID: 19150881
linkage; quantitative trait loci; twin; cardiovascular disease; thrombosis
21.  Toward a roadmap in global biobanking for health 
European Journal of Human Genetics  2012;20(11):1105-1111.
Biobanks can have a pivotal role in elucidating disease etiology, translation, and advancing public health. However, meeting these challenges hinges on a critical shift in the way science is conducted and requires biobank harmonization. There is growing recognition that a common strategy is imperative to develop biobanking globally and effectively. To help guide this strategy, we articulate key principles, goals, and priorities underpinning a roadmap for global biobanking to accelerate health science, patient care, and public health. The need to manage and share very large amounts of data has driven innovations on many fronts. Although technological solutions are allowing biobanks to reach new levels of integration, increasingly powerful data-collection tools, analytical techniques, and the results they generate raise new ethical and legal issues and challenges, necessitating a reconsideration of previous policies, practices, and ethical norms. These manifold advances and the investments that support them are also fueling opportunities for biobanks to ultimately become integral parts of health-care systems in many countries. International harmonization to increase interoperability and sustainability are two strategic priorities for biobanking. Tackling these issues requires an environment favorably inclined toward scientific funding and equipped to address socio-ethical challenges. Cooperation and collaboration must extend beyond systems to enable the exchange of data and samples to strategic alliances between many organizations, including governmental bodies, funding agencies, public and private science enterprises, and other stakeholders, including patients. A common vision is required and we articulate the essential basis of such a vision herein.
doi:10.1038/ejhg.2012.96
PMCID: PMC3477856  PMID: 22713808
22.  Genome-Wide Screen for Metabolic Syndrome Susceptibility Loci Reveals Strong Lipid Gene Contribution but No Evidence for Common Genetic Basis for Clustering of Metabolic Syndrome Traits 
Background
Genome-wide association (GWA) studies have identified several susceptibility loci for metabolic syndrome (MetS) component traits, but have had variable success in identifying susceptibility loci to the syndrome as an entity. We conducted a GWA study on MetS and its component traits in four Finnish cohorts consisting of 2637 MetS cases and 7927 controls, both free of diabetes, and followed the top loci in an independent sample with transcriptome and NMR-based metabonomics data. Furthermore, we tested for loci associated with multiple MetS component traits using factor analysis and built a genetic risk score for MetS.
Methods and Results
A previously known lipid locus, APOA1/C3/A4/A5 gene cluster region (SNP rs964184), was associated with MetS in all four study samples (P=7.23×10−9 in meta-analysis). The association was further supported by serum metabolite analysis, where rs964184 associated with various VLDL, TG, and HDL metabolites (P=0.024-1.88×10−5). Twenty-two previously identified susceptibility loci for individual MetS component traits were replicated in our GWA and factor analysis. Most of these associated with lipid phenotypes and none with two or more uncorrelated MetS components. A genetic risk score, calculated as the number of alleles in loci associated with individual MetS traits, was strongly associated with MetS status.
Conclusions
Our findings suggest that genes from lipid metabolism pathways have the key role in the genetic background of MetS. We found little evidence for pleiotropy linking dyslipidemia and obesity to the other MetS component traits such as hypertension and glucose intolerance.
doi:10.1161/CIRCGENETICS.111.961482
PMCID: PMC3378651  PMID: 22399527
metabolic syndrome; risk factors; genome-wide association study; meta-analysis; lipids
23.  Genome-Wide Association Studies of Asthma in Population-Based Cohorts Confirm Known and Suggested Loci and Identify an Additional Association near HLA 
PLoS ONE  2012;7(9):e44008.
Rationale
Asthma has substantial morbidity and mortality and a strong genetic component, but identification of genetic risk factors is limited by availability of suitable studies.
Objectives
To test if population-based cohorts with self-reported physician-diagnosed asthma and genome-wide association (GWA) data could be used to validate known associations with asthma and identify novel associations.
Methods
The APCAT (Analysis in Population-based Cohorts of Asthma Traits) consortium consists of 1,716 individuals with asthma and 16,888 healthy controls from six European-descent population-based cohorts. We examined associations in APCAT of thirteen variants previously reported as genome-wide significant (P<5x10−8) and three variants reported as suggestive (P<5×10−7). We also searched for novel associations in APCAT (Stage 1) and followed-up the most promising variants in 4,035 asthmatics and 11,251 healthy controls (Stage 2). Finally, we conducted the first genome-wide screen for interactions with smoking or hay fever.
Main Results
We observed association in the same direction for all thirteen previously reported variants and nominally replicated ten of them. One variant that was previously suggestive, rs11071559 in RORA, now reaches genome-wide significance when combined with our data (P = 2.4×10−9). We also identified two genome-wide significant associations: rs13408661 near IL1RL1/IL18R1 (PStage1+Stage2 = 1.1x10−9), which is correlated with a variant recently shown to be associated with asthma (rs3771180), and rs9268516 in the HLA region (PStage1+Stage2 = 1.1x10−8), which appears to be independent of previously reported associations in this locus. Finally, we found no strong evidence for gene-environment interactions with smoking or hay fever status.
Conclusions
Population-based cohorts with simple asthma phenotypes represent a valuable and largely untapped resource for genetic studies of asthma.
doi:10.1371/journal.pone.0044008
PMCID: PMC3461045  PMID: 23028483
24.  Novel Loci for Metabolic Networks and Multi-Tissue Expression Studies Reveal Genes for Atherosclerosis 
PLoS Genetics  2012;8(8):e1002907.
Association testing of multiple correlated phenotypes offers better power than univariate analysis of single traits. We analyzed 6,600 individuals from two population-based cohorts with both genome-wide SNP data and serum metabolomic profiles. From the observed correlation structure of 130 metabolites measured by nuclear magnetic resonance, we identified 11 metabolic networks and performed a multivariate genome-wide association analysis. We identified 34 genomic loci at genome-wide significance, of which 7 are novel. In comparison to univariate tests, multivariate association analysis identified nearly twice as many significant associations in total. Multi-tissue gene expression studies identified variants in our top loci, SERPINA1 and AQP9, as eQTLs and showed that SERPINA1 and AQP9 expression in human blood was associated with metabolites from their corresponding metabolic networks. Finally, liver expression of AQP9 was associated with atherosclerotic lesion area in mice, and in human arterial tissue both SERPINA1 and AQP9 were shown to be upregulated (6.3-fold and 4.6-fold, respectively) in atherosclerotic plaques. Our study illustrates the power of multi-phenotype GWAS and highlights candidate genes for atherosclerosis.
Author Summary
In this study, we aim to identify novel genetic variants for metabolism, characterize their effects on nearby genes, and show that the nearby genes are associated with metabolism and atherosclerosis. To discover new genetic variants, we use an alternative approach to traditional genome-wide association studies: we leverage the information in phenotype covariance to increase our statistical power. We identify variants at seven novel loci and then show that our top signals drive expression of nearby genes AQP9 and SERPINA1 in multiple tissues. We demonstrate that AQP9 and SERPINA1 gene expression, in turn, is associated with metabolite levels. Finally, we show that the genes are associated with atherosclerosis using mouse atherosclerotic lesion size (AQP9) as well as tissue from healthy human arteries and atherosclerotic plaques (AQP9 and SERPINA1). This study illustrates that multivariate analysis of correlated metabolites can boost power for gene discovery substantially. Further functional work will need to be performed to elucidate the biological role of SERPINA1 and AQP9 in atherosclerosis.
doi:10.1371/journal.pgen.1002907
PMCID: PMC3420921  PMID: 22916037
25.  Phenotype mining in CNV carriers from a population cohort† 
Human Molecular Genetics  2011;20(13):2686-2695.
Phenotype mining is a novel approach for elucidating the genetic basis of complex phenotypic variation. It involves a search of rich phenotype databases for measures correlated with genetic variation, as identified in genome-wide genotyping or sequencing studies. An initial implementation of phenotype mining in a prospective unselected population cohort, the Northern Finland 1966 Birth Cohort (NFBC1966), identifies neurodevelopment-related traits—intellectual deficits, poor school performance and hearing abnormalities—which are more frequent among individuals with large (>500 kb) deletions than among other cohort members. Observation of extensive shared single nucleotide polymorphism haplotypes around deletions suggests an opportunity to expand phenotype mining from cohort samples to the populations from which they derive.
doi:10.1093/hmg/ddr162
PMCID: PMC3110003  PMID: 21505072

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