Is There a Free Lunch in Inference?

The field of psychology, including cognitive science, is vexed by a crisis of confidence. Although the causes and solutions are varied, we focus here on a common logical problem in inference. The default mode of inference is significance testing, which has a free lunch property where researchers need not make detailed assumptions about the alternative to test the null hypothesis. We present the argument that there is no free lunch; that is, valid testing requires that researchers test the null against a well-specified alternative. We show how this requirement follows from the basic tenets of conventional and Bayesian probability. Moreover, we show in both the conventional and Bayesian framework that not specifying the alternative may lead to rejections of the null hypothesis with scant evidence. We review both frequentist and Bayesian approaches to specifying alternatives, and we show how such specifications improve inference. The field of cognitive science will benefit because consideration of reasonable alternatives will undoubtedly sharpen the intellectual underpinnings of research

Epigenome-wide association study of triglyceride postprandial responses to a high-fat dietary challenge

Postprandial lipemia (PPL), the increased plasma TG concentration after consuming a high-fat meal, is an independent risk factor for CVD. Individual responses to a meal high in fat vary greatly, depending on genetic and lifestyle factors. However, only a few loci have been associated with TG-PPL response. Heritable epigenomic changes may be significant contributors to the unexplained inter-individual PPL variability. We conducted an epigenome-wide association study on 979 subjects with DNA methylation measured from CD4(+) T cells, who were challenged with a high-fat meal as a part of the Genetics of Lipid Lowering Drugs and Diet Network study. Eight methylation sites encompassing five genes, LPP, CPT1A, APOA5, SREBF1, and ABCG1, were significantly associated with PPL response at an epigenome-wide level (P < 1.1 × 10(−7)), but no methylation site reached epigenome-wide significance after adjusting for baseline TG levels. Higher methylation at LPP, APOA5, SREBF1, and ABCG1, and lower methylation at CPT1A methylation were correlated with an increased TG-PPL response. These PPL-associated methylation sites, also correlated with fasting TG, account for a substantially greater amount of phenotypic variance (14.9%) in PPL and fasting TG (16.3%) when compared with the genetic contribution of loci identified by our previous genome-wide association study (4.5%). In summary, the epigenome is a large contributor to the variation in PPL, and this has the potential to be used to modulate PPL and reduce CVD

Offspring's leukocyte telomere length, paternal age, and telomere elongation in sperm.

PublishedJournal ArticleResearch Support, N.I.H., ExtramuralResearch Support, Non-U.S. Gov'tThis is the final version of the article. Available from Public Library of Science via the DOI in this record.Leukocyte telomere length (LTL) is a complex genetic trait. It shortens with age and is associated with a host of aging-related disorders. Recent studies have observed that offspring of older fathers have longer LTLs. We explored the relation between paternal age and offspring's LTLs in 4 different cohorts. Moreover, we examined the potential cause of the paternal age on offspring's LTL by delineating telomere parameters in sperm donors. We measured LTL by Southern blots in Caucasian men and women (n=3365), aged 18-94 years, from the Offspring of the Framingham Heart Study (Framingham Offspring), the NHLBI Family Heart Study (NHLBI-Heart), the Longitudinal Study of Aging Danish Twins (Danish Twins), and the UK Adult Twin Registry (UK Twins). Using Southern blots, Q-FISH, and flow-FISH, we also measured telomere parameters in sperm from 46 young (50 years) donors. Paternal age had an independent effect, expressed by a longer LTL in males of the Framingham Offspring and Danish Twins, males and females of the NHLBI-Heart, and females of UK Twins. For every additional year of paternal age, LTL in offspring increased at a magnitude ranging from half to more than twice of the annual attrition in LTL with age. Moreover, sperm telomere length analyses were compatible with the emergence in older men of a subset of sperm with elongated telomeres. Paternal age exerts a considerable effect on the offspring's LTL, a phenomenon which might relate to telomere elongation in sperm from older men. The implications of this effect deserve detailed study.Supported by NIH grants R01-AG021593, R01-AG020132, and P01-AG0876. Support was also provided by NIH contract NOHC25195, the NHLBI cooperative agreement grants U01 HL 67893, U01 HL67894, U01 HL67895, U01 HL67896, U01 HL67897, U01 HL67898, U01 HL67899, U01 HL67900, U01 HL67901, U01 HL67902, U01 HL56563, U01 HL56564, U01 HL56565, U01 HL56566, U01 HL56567, U01 HL56568, and U01 HL56569. Also funded in part by the Wellcome Trust grant (ref 074951)

Genetic analysis of long-lived families reveals novel variants influencing high density-lipoprotein cholesterol

The plasma levels of high-density lipoprotein cholesterol (HDL) have an inverse relationship to the risks of atherosclerosis and cardiovascular disease, and have also been associated with longevity. We sought to identify novel loci for HDL that could potentially provide new insights into biological regulation of HDL metabolism in healthy-longevous subjects. We performed a genome-wide association scan on HDL using a mixed model approach to account for family structure using kinship coefficients. A total of 4,114 subjects of European descent (480 families) were genotyped at ~2.3 million SNPs and ~38 million SNPs were imputed using the 1000 Genome Cosmopolitan reference panel in MACH. We identified novel variants near-NLRP1 (17p13) associated with an increase of HDL levels at genome-wide significant level (p< 5.0E-08). Additionally, several CETP (16q21) and ZNF259-APOA5-A4-C3-A1 (11q23.3) variants associated with HDL were found, replicating those previously reported in the literature. A possible regulatory variant upstream of NLRP1 that is associated with HDL in these elderly LLFS subjects may also contribute to their longevity and health. Our NLRP1 intergenic SNPs show a potential regulatory function in ENCODE; however, it is not clear whether they regulate NLRP1 or other more remote gene. NLRP1 plays an important role in the induction of apoptosis, and its inflammasome is critical for mediating innate immune responses. Nlrp1a (a mouse ortholog of human NLRP1) interacts with SREBP-1a (17p11) which has a fundamental role in lipid concentration and composition, and is involved in innate immune response in macrophages. The NLRP1 region is conserved in mammals, but also has evolved adaptively showing signals of positive selection in European populations that might confer an advantage. NLRP1 intergenic SNPs have also been associated with immunity/inflammasome disorders which highlights the biological importance of this chromosomal region

Trade-offs in the effects of the apolipoprotein E polymorphism on risks of diseases of the heart, cancer, and neurodegenerative disorders: Insights on mechanisms from the long life family study

The lack of evolutionary established mechanisms linking genes to age-related traits makes the problem of genetic susceptibility to health span inherently complex. One complicating factor is genetic trade-off. Here we focused on long-living participants of the Long Life Family Study (LLFS), their offspring, and spouses to: (1) Elucidate whether trade-offs in the effect of the apolipoprotein E e4 allele documented in the Framingham Heart Study (FHS) are a more general phenomenon, and (2) explore potential mechanisms generating age- and gender-specific trade-offs in the effect of the e4 allele on cancer, diseases of the heart, and neurodegenerative disorders assessed retrospectively in the LLFS populations. The e4 allele can diminish risks of cancer and diseases of the heart and confer risks of diseases of the heart in a sex-, age-, and LLFS-population-specific manner. A protective effect against cancer is seen in older long-living men and, potentially, their sons (>75 years, relative risk [RR](>75)=0.48, p=0.086), which resembles our findings in the FHS. The protective effect against diseases of the heart is limited to long-living older men (RR(>76)=0.50, p=0.016), as well. A detrimental effect against diseases of the heart is characteristic for a normal LLFS population of male spouses and is specific for myocardial infarction (RR=3.07, p=2.1×10(−3)). These trade-offs are likely associated with two inherently different mechanisms, including disease-specific (detrimental; characteristic for a normal male population) and systemic, aging-related (protective; characteristic for older long-living men) mechanisms. The e4 allele confers risks of neurological disorders in men and women (RR=1.98, p=0.046). The results highlight the complex role of the e4 allele in genetic susceptibility to health span

TRAIL in the mandarin fish Siniperca chuatsi: Gene and its apoptotic effect in HeLa cells

Tumor necrosis factor (TNF)-related apoptosis-inducing ligand (TRAIL) is one of the TNF superfamily members, participating in many biological processes including cell proliferation and apoptotic death. In this study, a TRAIL gene was cloned from a perciform fish, the mandarin fish Siniperca chuatsi, a major cultured fish in China's aquaculture, and is named as SCTRAIL for S. chuatsi TRAIL. The full-length cDNA of SCTRAIL is 1359 bp, encoding a 283-amino-acid protein. This deduced protein contains the CYS231, a 23-mer fragment of transmembrane region, a glycosylation site and a TNF family signature, all of which are conserved among TRAIL members. SCTRAIL gene consists of six exons, with five intervening introns, spaced over approximately 9 kb of genomic sequence. Southern blotting demonstrated that the SCTRAIL gene is present as a single copy in mandarin fish genome. A 620 bp promoter region obtained by genome walking contains a number of putative transcription factor binding sites, such as Oct-1, Sp-1, NF-1, RAP-1, C/EBPaLp, NF-kappa B and AP-1. The SCTRAIL is constitutively expressed in all the analyzed tissues, as revealed by RT-PCR, which is confirmed by Western blotting analysis using polyclonal antibody against bacteria-derived recombinant SCTRAIL protein. As an apoptosis-inducing ligand, the overexpression of SCTRAIL but not the mutant SCTRAIL-C203S in HeLa cells induced changes characteristic of apoptosis, including chromatin condensation, nucleus fragmentation, DNA ladder, and increase of sub-G0/G1 cells in FACS analysis. (c) 2007 Elsevier Ltd. All rights reserved.Tumor necrosis factor (TNF)-related apoptosis-inducing ligand (TRAIL) is one of the TNF superfamily members, participating in many biological processes including cell proliferation and apoptotic death. In this study, a TRAIL gene was cloned from a perciform fish, the mandarin fish Siniperca chuatsi, a major cultured fish in China's aquaculture, and is named as SCTRAIL for S. chuatsi TRAIL. The full-length cDNA of SCTRAIL is 1359 bp, encoding a 283-amino-acid protein. This deduced protein contains the CYS231, a 23-mer fragment of transmembrane region, a glycosylation site and a TNF family signature, all of which are conserved among TRAIL members. SCTRAIL gene consists of six exons, with five intervening introns, spaced over approximately 9 kb of genomic sequence. Southern blotting demonstrated that the SCTRAIL gene is present as a single copy in mandarin fish genome. A 620 bp promoter region obtained by genome walking contains a number of putative transcription factor binding sites, such as Oct-1, Sp-1, NF-1, RAP-1, C/EBPaLp, NF-kappa B and AP-1. The SCTRAIL is constitutively expressed in all the analyzed tissues, as revealed by RT-PCR, which is confirmed by Western blotting analysis using polyclonal antibody against bacteria-derived recombinant SCTRAIL protein. As an apoptosis-inducing ligand, the overexpression of SCTRAIL but not the mutant SCTRAIL-C203S in HeLa cells induced changes characteristic of apoptosis, including chromatin condensation, nucleus fragmentation, DNA ladder, and increase of sub-G0/G1 cells in FACS analysis. (c) 2007 Elsevier Ltd. All rights reserved

Genome wide association and linkage analyses identified three loci-4q25, 17q23.2, and 10q11.21-associated with variation in leukocyte telomere length: the Long Life Family Study

Leukocyte telomere length is believed to measure cellular aging in humans, and short leukocyte telomere length is associated with increased risks of late onset diseases, including cardiovascular disease, dementia, etc. Many studies have shown that leukocyte telomere length is a heritable trait, and several candidate genes have been identified, including TERT, TERC, OBFC1, and CTC1. Unlike most studies that have focused on genetic causes of chronic diseases such as heart disease and diabetes in relation to leukocyte telomere length, the present study examined the genome to identify variants that may contribute to variation in leukocyte telomere length among families with exceptional longevity. From the genome wide association analysis in 4,289 LLFS participants, we identified a novel intergenic SNP rs7680468 located near PAPSS1 and DKK2 on 4q25 (p = 4.7E-8). From our linkage analysis, we identified two additional novel loci with HLOD scores exceeding three, including 4.77 for 17q23.2, and 4.36 for 10q11.21. These two loci harbor a number of novel candidate genes with SNPs, and our gene-wise association analysis identified multiple genes, including DCAF7, POLG2, CEP95, and SMURF2 at 17q23.2; and RASGEF1A, HNRNPF, ANF487, CSTF2T, and PRKG1 at 10q11.21. Among these genes, multiple SNPs were associated with leukocyte telomere length, but the strongest association was observed with one contiguous haplotype in CEP95 and SMURF2. We also show that three previously reported genes—TERC, MYNN, and OBFC1—were significantly associated with leukocyte telomere length at p(empirical) < 0.05

Ig heavy chain genes and their locus in grass carp Ctenopharyngodon idella

The cDNA and genomic sequences of IgD and IgZ were characterized in grass carp Ctenopharyngodon idella in the present study, and with the identification of a BAC clone covering zeta, mu, and delta genes, the IgH locus containing these Ig genes and other V, D, J genes was also illustrated in this fish. Secretory and membrane-bound IgZ were identified, with two transmembrane exons spliced within the CH4 exon, as reported in IgM of mammals and IgZ in other teleost fish. The first and second constant domains of IgZ shows more than 90% nucleotide identity with respective domains of grass carp IgM. The IgD has a structure of delta 1-(delta 2-delta 3-delta 4)(2)-delta 5-delta 6-delta 7-TM-UTR, with the repeat of delta 2-delta 3-delta 4; but intron was not found between the two repeat, i.e. between the first delta 2-delta 3-delta 4 (delta 2.1-delta 3.1-delta 4.1) and the second delta 2-delta 3-delta 4 (delta 2.2-delta 3.2-delta 4.2), and the intron between delta 3.1 and delta 4.1 was much shorter than the intron between delta 3.2 and delta 4.2. The genomic organization of the IgH locus has a pattern of Vn-Dn-Jn-C zeta-Dn-Jn-C mu-C delta, as reported in other teleost fish. Thirteen V-H, fourteen D, and twelve J(H) genes were observed in this locus, with the similarity of three D segments and four J(H) segments being the same in the upstream of C zeta, and C mu. The transcriptional enhancer located at the mu-delta intergenic region was also analyzed and it seems possible that this enhancer is functional as verified in zebrafish and channel catfish. (C) 2010 Elsevier Ltd. All rights reserved

General Framework for Meta-Analysis of Haplotype Association Tests

For complex traits, most associated single nucleotide variants (SNV) discovered to date have a small effect, and detection of association is only possible with large sample sizes. Because of patient confidentiality concerns, it is often not possible to pool genetic data from multiple cohorts, and meta-analysis has emerged as the method of choice to combine results from multiple studies. Many meta-analysis methods are available for single SNV analyses. As new approaches allow the capture of low frequency and rare genetic variation, it is of interest to jointly consider multiple variants to improve power. However, for the analysis of haplotypes formed by multiple SNVs, meta-analysis remains a challenge, because different haplotypes may be observed across studies. We propose a two-stage meta-analysis approach to combine haplotype analysis results. In the first stage, each cohort estimate haplotype effect sizes in a regression framework, accounting for relatedness among observations if appropriate. For the second stage, we use a multivariate generalized least square meta-analysis approach to combine haplotype effect estimates from multiple cohorts. Haplotype-specific association tests and a global test of independence between haplotypes and traits are obtained within our framework. We demonstrate through simulation studies that we control the type-I error rate, and our approach is more powerful than inverse variance weighted meta-analysis of single SNV analysis when haplotype effects are present. We replicate a published haplotype association between fasting glucose-associated locus (G6PC2) and fasting glucose in seven studies from the Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium and we provide more precise haplotype effect estimates.Generation Scotland: Generation Scotland received core funding from the Chief Scientist Office of the Scottish Government Health Directorate CZD/16/6 and the Scottish Funding Council HR03006. Genotyping of the GS:SFHS samples was carried out by the Genetics Core Laboratory at the Wellcome Trust Clinical Research Facility, Edinburgh, Scotland, and was funded by the UKâs Medical Research Council. Ethics approval for the study was given by the NHS Tayside committee on research ethics (reference 05/S1401/89). We are grateful to all the families who took part, the general practitioners and the Scottish School of Primary Care for their help in recruiting them, and the whole Generation Scotland team, which includes interviewers, computer and laboratory technicians, clerical workers, research scientists, volunteers, managers, receptionists, healthcare assistants and nurses. FamHS: Family Heart Study was supported by NIH grants RO1-HL-087700 and RO1-HL-088215 (M.A.P., PI) from NHLBI, and RO1-DK-8925601 and RO1-DK-075681 (I.B.B., PI) from NIDDK. MESA: MESA and the MESA SHARe project are conducted and supported by the National Heart, Lung, and Blood Institute (NHLBI) in collaboration with MESA investigators. Support for MESA is provided by contracts N01-HC-95159, N01-HC-95160, N01-HC-95161, N01-HC-95162, N01-HC-95163, N01-HC-95164, N01-HC-95165, N01-HC-95166, N01-HC-95167, N01-HC-95168, N01-HC-95169, UL1-TR-001079, and UL1-TR-000040. Funding for SHARe genotyping was provided by NHLBI contract N02-HL-64278. Funding for MESA Family was provided by grants R01-HL-071051, R01-HL-071205, R01-HL-071250, R01-HL-071251, R01-HL-071252, R01-HL-071258, R01-HL-071259, and UL1-RR-025005. The provision of genotyping data was supported in part by the National Center for Advancing Translational Sciences, CTSI grant UL1TR000124, and the National Institute of Diabetes and Digestive and Kidney Disease Diabetes Research Center (DRC) grant DK063491 to the Southern California Diabetes Endocrinology Research Center. FHS: Framingham Heart Study—Genotyping, quality control, and calling of the Illumina HumanExome BeadChip in the Framingham Heart Study was supported by funding from the National Heart, Lung and Blood Institute, Division of Intramural Research (Daniel Levy and Christopher J. OâDonnell, Principle Investigators). A portion of this research was conducted using the Linux Clusters for Genetic Analysis (LinGA) computing resources at Boston University Medical Campus. Also supported by National Institute for Diabetes and Digestive and Kidney Diseases (NIDDK) R01 DK078616, NIDDK K24 DK080140, and American Diabetes Association Mentor-Based Postdoctoral Fellowship Award #7-09-MN-32, all to Dr. Meigs. FENLAND: The Fenland Study is funded by the Medical Research Council (MC_U106179471) and Wellcome Trust. We are grateful to all the volunteers for their time and help, and to the General Practitioners and practice staff for assistance with recruitment. We thank the Fenland Study Investigators, Fenland Study Co-ordination team, and the Epidemiology Field, Data and Laboratory teams. EPIC-Potsdam: We thank all EPIC-Potsdam participants for their invaluable contribution to the study. The study was supported in part by a grant from the German Federal Ministry of Education and Research (BMBF) to the German Center for Diabetes Research (DZD e.V.). The recruitment phase of the EPIC-Potsdam study was supported by the Federal Ministry of Science, Germany (01 EA 9401) and the European Union (SOC 95201408 05 F02). The follow-up of the EPIC-Potsdam study was supported by German Cancer Aid (70-2488-Ha I) and the European Community (SOC 98200769 05 F02). Furthermore, we thank Dr. Manuela Bergmann who was responsible for the methodological and organizational work of data collections of exposures and outcomes and Wolfgang Fleischhauer for his medical expertise that was employed in case ascertainment and contacts with the physicians and Ellen Kohlsdorf for data management. CHS: This CHS research was supported by NHLBI contracts HHSN268201200036C, HHSN268200800007C, N01HC55222, N01HC85079, N01HC85080, N01HC85081, N01HC85082, N01HC85083, N01HC85086; and NHLBI grants HL080295, HL087652, HL103612, HL068986 with additional contribution from the National Institute of Neurological Disorders and Stroke (NINDS). Additional support was provided through AG023629 from the National Institute on Aging (NIA). A full list of CHS investigators and institutions can be found at http://www.chs-nhlbi.org/pi.htm. The provision of genotyping data was supported in part by the National Center for Advancing Translational Sciences, CTSI grant UL1TR000124, and the National Institute of Diabetes and Digestive and Kidney Disease Diabetes Research Center (DRC) grant DK063491 to the Southern California Diabetes Endocrinology Research Center. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.This is the final version of the article. It first appeared from Wiley via http://dx.doi.org/10.1002/gepi.2195