Novel associations for hypothyroidism include known autoimmune risk loci

Hypothyroidism is the most common thyroid disorder, affecting about 5% of the general population. Here we present the first large genome-wide association study of hypothyroidism, in 2,564 cases and 24,448 controls from the customer base of 23andMe, Inc., a personal genetics company. We identify four genome-wide significant associations, two of which are well known to be involved with a large spectrum of autoimmune diseases: rs6679677 near _PTPN22_ and rs3184504 in _SH2B3_ (p-values 3.5e-13 and 3.0e-11, respectively). We also report associations with rs4915077 near _VAV3_ (p-value 8.3e-11), another gene involved in immune function, and rs965513 near _FOXE1_ (p-value 3.1e-14). Of these, the association with _PTPN22_ confirms a recent small candidate gene study, and _FOXE1_ was previously known to be associated with thyroid-stimulating hormone (TSH) levels. Although _SH2B3_ has been previously linked with a number of autoimmune diseases, this is the first report of its association with thyroid disease. The _VAV3_ association is novel. These results suggest heterogeneity in the genetic etiology of hypothyroidism, implicating genes involved in both autoimmune disorders and thyroid function. Using a genetic risk profile score based on the top association from each of the four genome-wide significant regions in our study, the relative risk between the highest and lowest deciles of genetic risk is 2.1

Dissociation of accumulated genetic risk and disease severity in patients with schizophrenia

Genotype–phenotype correlations of common monogenic diseases revealed that the degree of deviation of mutant genes from wild-type structure and function often predicts disease onset and severity. In complex disorders such as schizophrenia, the overall genetic risk is still often >50% but genotype–phenotype relationships are unclear. Recent genome-wide association studies (GWAS) replicated a risk for several single-nucleotide polymorphisms (SNPs) regarding the endpoint diagnosis of schizophrenia. The biological relevance of these SNPs, however, for phenotypes or severity of schizophrenia has remained obscure. We hypothesized that the GWAS ‘top-10' should as single markers, but even more so upon their accumulation, display associations with lead features of schizophrenia, namely positive and negative symptoms, cognitive deficits and neurological signs (including catatonia), and/or with age of onset of the disease prodrome as developmental readout and predictor of disease severity. For testing this hypothesis, we took an approach complementary to GWAS, and performed a phenotype-based genetic association study (PGAS). We utilized the to our knowledge worldwide largest phenotypical database of schizophrenic patients (n>1000), the GRAS (Göttingen Research Association for Schizophrenia) Data Collection. We found that the ‘top-10' GWAS-identified risk SNPs neither as single markers nor when explored in the sense of a cumulative genetic risk, have any predictive value for disease onset or severity in the schizophrenic patients, as demonstrated across all core symptoms. We conclude that GWAS does not extract disease genes of general significance in schizophrenia, but may yield, on a hypothesis-free basis, candidate genes relevant for defining disease subgroups

Essential versus accessory aspects of cell death: recommendations of the NCCD 2015

Cells exposed to extreme physicochemical or mechanical stimuli die in an uncontrollable manner, as a result of their immediate structural breakdown. Such an unavoidable variant of cellular demise is generally referred to as ‘accidental cell death’ (ACD). In most settings, however, cell death is initiated by a genetically encoded apparatus, correlating with the fact that its course can be altered by pharmacologic or genetic interventions. ‘Regulated cell death’ (RCD) can occur as part of physiologic programs or can be activated once adaptive responses to perturbations of the extracellular or intracellular microenvironment fail. The biochemical phenomena that accompany RCD may be harnessed to classify it into a few subtypes, which often (but not always) exhibit stereotyped morphologic features. Nonetheless, efficiently inhibiting the processes that are commonly thought to cause RCD, such as the activation of executioner caspases in the course of apoptosis, does not exert true cytoprotective effects in the mammalian system, but simply alters the kinetics of cellular demise as it shifts its morphologic and biochemical correlates. Conversely, bona fide cytoprotection can be achieved by inhibiting the transduction of lethal signals in the early phases of the process, when adaptive responses are still operational. Thus, the mechanisms that truly execute RCD may be less understood, less inhibitable and perhaps more homogeneous than previously thought. Here, the Nomenclature Committee on Cell Death formulates a set of recommendations to help scientists and researchers to discriminate between essential and accessory aspects of cell death

The role of height-associated loci identified in genome wide association studies in the determination of pediatric stature

<p>Abstract</p> <p>Background</p> <p>Human height is considered highly heritable and correlated with certain disorders, such as type 2 diabetes and cancer. Despite environmental influences, genetic factors are known to play an important role in stature determination. A number of genetic determinants of adult height have already been established through genome wide association studies.</p> <p>Methods</p> <p>To examine 51 single nucleotide polymorphisms (SNPs) corresponding to the 46 previously reported genomic loci for height in 8,184 European American children with height measurements. We leveraged genotyping data from our ongoing GWA study of height variation in children in order to query the 51 SNPs in this pediatric cohort.</p> <p>Results</p> <p>Sixteen of these SNPs yielded at least nominally significant association to height, representing fifteen different loci including <it>EFEMP1-PNPT1, GPR126, C6orf173, SPAG17</it>, Histone class 1, HLA class III and <it>GDF5-UQCC</it>. Other loci revealed no evidence for association, including <it>HMGA1 and HMGA2</it>. For the 16 associated variants, the genotype score explained 1.64% of the total variation for height z-score.</p> <p>Conclusion</p> <p>Among 46 loci that have been reported to associate with adult height to date, at least 15 also contribute to the determination of height in childhood.</p

Hundreds of variants clustered in genomic loci and biological pathways affect human height

Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P < 0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented among variants that alter amino-acid structure of proteins and expression levels of nearby genes. Our data explain approximately 10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to approximately 16% of phenotypic variation (approximately 20% of heritable variation). Although additional approaches are needed to dissect the genetic architecture of polygenic human traits fully, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways.

A Conserved Role for SNX9-Family Members in the Regulation of Phagosome Maturation during Engulfment of Apoptotic Cells

Clearance of apoptotic cells is of key importance during development, tissue homeostasis and wound healing in multi-cellular animals. Genetic studies in the nematode Caenorhabditis elegans have identified a set of genes involved in the early steps of cell clearance, in particular the recognition and internalization of apoptotic cells. A pathway that orchestrates the maturation of phagosomes containing ingested apoptotic cells in the worm has recently been described. However, many steps in this pathway remain elusive. Here we show that the C. elegans SNX9-family member LST-4 (lateral signaling target) and its closest mammalian orthologue SNX33 play an evolutionary conserved role during apoptotic cell corpse clearance. In lst-4 deficient worms, internalized apoptotic cells accumulated within non-acidified, DYN-1-positive but RAB-5-negative phagosomes. Genetically, we show that LST-4 functions at the same step as DYN-1 during corpse removal, upstream of the GTPase RAB-5. We further show that mammalian SNX33 rescue C. elegans lst-4 mutants and that overexpression of truncated SNX33 fragments interfered with phagosome maturation in a mammalian cell system. Taken together, our genetic and cell biological analyses suggest that LST-4 is recruited through a combined activity of DYN-1 and VPS-34 to the early phagosome membrane, where it cooperates with DYN-1 to promote recruitment/retention of RAB-5 on the early phagosomal membrane during cell corpse clearance. The functional conservation between LST-4 and SNX33 indicate that these early steps of apoptotic phagosome maturation are likely conserved through evolution

Testing the role of predicted gene knockouts in human anthropometric trait variation

National Heart, Lung, and Blood Institute (NHLBI) S.L. is funded by a Canadian Institutes of Health Research Banting doctoral scholarship. G.L. is funded by Genome Canada and Génome Québec; the Canada Research Chairs program; and the Montreal Heart Institute Foundation. C.M.L. is supported by Wellcome Trust (grant numbers 086596/Z/08/Z, 086596/Z/08/A); and the Li Ka Shing Foundation. N.S. is funded by National Institutes of Health (grant numbers HL088456, HL111089, HL116747). The Mount Sinai BioMe Biobank Program is supported by the Andrea and Charles Bronfman Philanthropies. GO ESP is supported by NHLBI (RC2 HL-103010 to HeartGO, RC2 HL-102923 to LungGO, RC2 HL-102924 to WHISP). The ESP exome sequencing was performed through NHLBI (RC2 HL-102925 to BroadGO, RC2 HL- 102926 to SeattleGO). EGCUT work was supported through the Estonian Genome Center of University of Tartu by the Targeted Financing from the Estonian Ministry of Science and Education (grant number SF0180142s08); the Development Fund of the University of Tartu (grant number SP1GVARENG); the European Regional Development Fund to the Centre of Excellence in Genomics (EXCEGEN) [grant number 3.2.0304.11-0312]; and through FP7 (grant number 313010). EGCUT were further supported by the US National Institute of Health (grant number R01DK075787). A.K.M. was supported by an American Diabetes Association Mentor-Based Postdoctoral Fellowship (#7-12-MN- 02). The BioVU dataset used in the analyses described were obtained from Vanderbilt University Medical Centers BioVU which is supported by institutional funding and by the Vanderbilt CTSA grant ULTR000445 from NCATS/NIH. Genome-wide genotyping was funded by NIH grants RC2GM092618 from NIGMS/OD and U01HG004603 from NHGRI/NIGMS. Funding to pay the Open Access publication charges for this article was provided by a block grant from Research Councils UK to the University of Cambridge

Testing the role of predicted gene knockouts in human anthropometric trait variation

National Heart, Lung, and Blood Institute (NHLBI) S.L. is funded by a Canadian Institutes of Health Research Banting doctoral scholarship. G.L. is funded by Genome Canada and Génome Québec; the Canada Research Chairs program; and the Montreal Heart Institute Foundation. C.M.L. is supported by Wellcome Trust (grant numbers 086596/Z/08/Z, 086596/Z/08/A); and the Li Ka Shing Foundation. N.S. is funded by National Institutes of Health (grant numbers HL088456, HL111089, HL116747). The Mount Sinai BioMe Biobank Program is supported by the Andrea and Charles Bronfman Philanthropies. GO ESP is supported by NHLBI (RC2 HL-103010 to HeartGO, RC2 HL-102923 to LungGO, RC2 HL-102924 to WHISP). The ESP exome sequencing was performed through NHLBI (RC2 HL-102925 to BroadGO, RC2 HL- 102926 to SeattleGO). EGCUT work was supported through the Estonian Genome Center of University of Tartu by the Targeted Financing from the Estonian Ministry of Science and Education (grant number SF0180142s08); the Development Fund of the University of Tartu (grant number SP1GVARENG); the European Regional Development Fund to the Centre of Excellence in Genomics (EXCEGEN) [grant number 3.2.0304.11-0312]; and through FP7 (grant number 313010). EGCUT were further supported by the US National Institute of Health (grant number R01DK075787). A.K.M. was supported by an American Diabetes Association Mentor-Based Postdoctoral Fellowship (#7-12-MN- 02). The BioVU dataset used in the analyses described were obtained from Vanderbilt University Medical Centers BioVU which is supported by institutional funding and by the Vanderbilt CTSA grant ULTR000445 from NCATS/NIH. Genome-wide genotyping was funded by NIH grants RC2GM092618 from NIGMS/OD and U01HG004603 from NHGRI/NIGMS. Funding to pay the Open Access publication charges for this article was provided by a block grant from Research Councils UK to the University of Cambridge

ASPP: a new family of oncogenes and tumour suppressor genes

The apoptosis stimulating proteins of p53 (ASPP) family consists of three members, ASPP1, ASPP2 and iASPP. They bind to proteins that are key players in controlling apoptosis (p53, Bcl-2 and RelA/p65) and cell growth (APCL, PP1). So far, the best-known function of the ASPP family members is their ability to regulate the apoptotic function of p53 and its family members, p63 and p73. Biochemical and genetic evidence has shown that ASPP1 and ASPP2 activate, whereas iASPP inhibits, the apoptotic but not the cell-cycle arrest function of p53. The p53 tumour suppressor gene, one of the most frequently mutated genes in human cancer, is capable of suppressing tumour growth through its ability to induce apoptosis or cell-cycle arrest. Thus, the ASPP family of proteins helps to determine how cells choose to die and may therefore be a novel target for cancer therapy