Examination of Candidate Exonic Variants for Association to Alzheimer Disease in the Amish

Alzheimer disease (AD) is the most common cause of dementia. As with many complex diseases, the identified variants do not explain the total expected genetic risk that is based on heritability estimates for AD. Isolated founder populations, such as the Amish, are advantageous for genetic studies as they overcome heterogeneity limitations associated with complex population studies. We determined that Amish AD cases harbored a significantly higher burden of the known risk alleles compared to Amish cognitively normal controls, but a significantly lower burden when compared to cases from a dataset of unrelated individuals. Whole-exome sequencing of a selected subset of the overall study population was used as a screening tool to identify variants located in the regions of the genome that are most likely to contribute risk. By then genotyping the top candidate variants from the known AD genes and from linkage regions implicated previous studies in the full dataset, new associations could be confirmed. The most significant result (p = 0.0012) was for rs73938538, a synonymous variant in LAMA1 within the previously identified linkage peak on chromosome 18. However, this association is specific to the Amish and did not generalize when tested in a dataset of unrelated individuals. These results suggest that additional risk variation in the Amish remains to be identified and likely resides outside of the classical protein coding gene regions.     

The role of gene polymorphisms in the pathogenesis of chronic obstructive pulmonary disease

Chronic obstructive pulmonary disease (COPD) is a major cause of morbidity and mortality worldwide. Irreversible airflow limitation, both progressive and associated with an inflammatory response of the lungs to noxious particles or gases, is a hallmark of the disease. Cigarette smoking is the most important environmental risk factor for COPD, nevertheless, only approximately 20–30% of smokers develop symptomatic disease. Epidemiological studies, case-control studies in relatives of patients with COPD, and twin studies suggest that COPD is a genetically complex disease with environmental factors and many involved genes interacting together. Two major strategies have been employed to identify the genes and the polymorphisms that likely contribute to the development of complex diseases: association studies and linkage analyses. Biologically plausible pathogenetic mechanisms are prerequisites to focus the search for genes of known function in association studies. Protease-antiprotease imbalance, generation of oxidative stress, and chronic inflammation are recognized as the principal mechanisms leading to irreversible airflow obstruction and parenchymal destruction in the lung. Therefore, genes which have been implicated in the pathogenesis of COPD are involved in antiproteolysis, antioxidant barrier and metabolism of xenobiotic substances, inflammatory response to cigarette smoke, airway hyperresponsiveness, and pulmonary vascular remodelling. Significant associations with COPD-related phenotypes have been reported for polymorphisms in genes coding for matrix metalloproteinases, microsomal epoxide hydrolase, glutathione-S-transferases, heme oxygenase, tumor necrosis factor, interleukines 1, 8, and 13, vitamin D-binding protein and β-2-adrenergic receptor (ADRB2), whereas adequately powered replication studies failed to confirm most of the previously observed associations. Genome-wide linkage analyses provide us with a novel tool to identify the general locations of COPD susceptibility genes, and should be followed by association analyses of positional candidate genes from COPD pathophysiology, positional candidate genes selected from gene expression studies, or dense single nucleotide polymorphism panels across regions of linkage. Haplotype analyses of genes with multiple polymorphic sites in linkage disequilibrium, such as the ADRB2 gene, provide another promising field that has yet to be explored in patients with COPD. In the present article we review the current knowledge about gene polymorphisms that have been recently linked to the risk of developing COPD and/or may account for variations in the disease course.     

Polymorphisms in the tyrosine kinase 2 and interferon regulatory factor 5 genes are associated with systemic lupus erythematosus

Systemic lupus erythematosus (SLE) is a complex systemic autoimmune disease caused by both genetic and environmental factors. Genome scans in families with SLE point to multiple potential chromosomal regions that harbor SLE susceptibility genes, and association studies in different populations have suggested several susceptibility alleles for SLE. Increased production of type I interferon (IFN) and expression of IFN-inducible genes is commonly observed in SLE and may be pivotal in the molecular pathogenesis of the disease. We analyzed 44 single-nucleotide polymorphisms (SNPs) in 13 genes from the type I IFN pathway in 679 Swedish, Finnish, and Icelandic patients with SLE, in 798 unaffected family members, and in 438 unrelated control individuals for joint linkage and association with SLE. In two of the genes—the tyrosine kinase 2 (TYK2) and IFN regulatory factor 5 (IRF5) genes—we identified SNPs that displayed strong signals in joint analysis of linkage and association (unadjusted P<10^-7) with SLE. TYK2 binds to the type I IFN receptor complex and IRF5 is a regulator of type I IFN gene expression. Thus, our results support a disease mechanism in SLE that involves key components of the type I IFN system.     

The Childhood Leukemia International Consortium

Background: Acute leukemia is the most common cancer in children under 15 years of age; 80% are acute lymphoblastic leukemia (ALL) and 17% are acute myeloid leukemia (AML). Childhood leukemia shows further diversity based on cytogenetic and molecular characteristics, which may relate to distinct etiologies. Case–control studies conducted worldwide, particularly of ALL, have collected a wealth of data on potential risk factors and in some studies, biospecimens. There is growing evidence for the role of infectious/immunologic factors, fetal growth, and several environmental factors in the etiology of childhood ALL. The risk of childhood leukemia, like other complex diseases, is likely to be influenced both by independent and interactive effects of genes and environmental exposures. While some studies have analyzed the role of genetic variants, few have been sufficiently powered to investigate gene–environment interactions. Objectives: The Childhood Leukemia International Consortium (CLIC) was established in 2007 to promote investigations of rarer exposures, gene–environment interactions and subtype-specific associations through the pooling of data from independent studies. Methods: By September 2012, CLIC included 22 studies (recruitment period: 1962–present) from 12 countries, totaling approximately 31 000 cases and 50 000 controls. Of these, 19 case–control studies have collected detailed epidemiologic data, and DNA samples have been collected from children and child–parent trios in 15 and 13 of these studies, respectively. Two registry-based studies and one study comprising hospital records routinely obtained at birth and/or diagnosis have limited interview data or biospecimens. Conclusions: CLIC provides a unique opportunity to fill gaps in knowledge about the role of environmental and genetic risk factors, critical windows of exposure, the effects of gene–environment interactions and associations among specific leukemia subtypes in different ethnic groups.     

Ordered subset linkage analysis based on admixture proportion identifies new linkage evidence for alcohol dependence in African-Americans

Genetic heterogeneity could reduce the power of linkage analysis to detect risk loci for complex traits such as alcohol dependence (AD). Previously, we performed a genomewide linkage analysis for AD in African-Americans (AAs) (Biol Psychiatry 65:111–115, 2009). The power of that linkage analysis could have been reduced by the presence of genetic heterogeneity owing to differences in admixture among AA families. We hypothesized that by examining a study sample whose genetic ancestry was more homogeneous, we could increase the power to detect linkage. To test this hypothesis, we performed ordered subset linkage analysis in 384 AA families using admixture proportion as a covariate to identify a more homogeneous subset of families and determine whether there is increased evidence for linkage with AD. Statistically significant increases in lod scores in subsets relative to the overall sample were identified on chromosomes 4 (P = 0.0001), 12 (P = 0.021), 15 (P = 0.026) and 22 (P = 0.0069). In a subset of 44 families with African ancestry proportions ranging from 0.858 to 0.996, we observed a genomewide significant linkage at 180 cM on chromosome 4 (lod = 4.24, pointwise P < 0.00001, empirical genomewide P = 0.008). A promising candidate gene located there, GLRA3, which encodes a subunit of the glycine neurotransmitter receptor. Our results demonstrate that admixture proportion can be used as a covariate to reduce genetic heterogeneity and enhance the detection of linkage for AD in an admixed population such as AAs. This approach could be applied to any linkage analysis for complex traits conducted in an admixed population.     

A Genomewide Scan Identifies Two Novel Loci Involved in Specific Language Impairment

Approximately 4% of English-speaking children are affected by specific language impairment (SLI), a disorder in the development of language skills despite adequate opportunity and normal intelligence. Several studies have indicated the importance of genetic factors in SLI; a positive family history confers an increased risk of development, and concordance in monozygotic twins consistently exceeds that in dizygotic twins. However, like many behavioral traits, SLI is assumed to be genetically complex, with several loci contributing to the overall risk. We have compiled 98 families drawn from epidemiological and clinical populations, all with probands whose standard language scores fall 1.5 SD below the mean for their age. Systematic genomewide quantitative-trait–locus analysis of three language-related measures (i.e., the Clinical Evaluation of Language Fundamentals–Revised [CELF-R] receptive and expressive scales and the nonword repetition [NWR] test) yielded two regions, one on chromosome 16 and one on 19, that both had maximum LOD scores of 3.55. Simulations suggest that, of these two multipoint results, the NWR linkage to chromosome 16q is the most significant, with empirical P values reaching 10⁻⁵, under both Haseman-Elston (HE) analysis (LOD score 3.55; P=.00003) and variance-components (VC) analysis (LOD score 2.57; P=.00008). Single-point analyses provided further support for involvement of this locus, with three markers, under the peak of linkage, yielding LOD scores >1.9. The 19q locus was linked to the CELF-R expressive-language score and exceeds the threshold for suggestive linkage under all types of analysis performed—multipoint HE analysis (LOD score 3.55; empirical P=.00004) and VC (LOD score 2.84; empirical P=.00027) and single-point HE analysis (LOD score 2.49) and VC (LOD score 2.22). Furthermore, both the clinical and epidemiological samples showed independent evidence of linkage on both chromosome 16q and chromosome 19q, indicating that these may represent universally important loci in SLI and, thus, general risk factors for language impairment.     

The HDAC9-associated risk locus promotes coronary artery disease by governing TWIST1

Genome wide association studies (GWAS) have identified thousands of single nucleotide polymorphisms (SNPs) associated with the risk of common disorders. However, since the large majority of these risk SNPs reside outside gene-coding regions, GWAS generally provide no information about causal mechanisms regarding the specific gene(s) that are affected or the tissue(s) in which these candidate gene(s) exert their effect. The ‘gold standard’ method for understanding causal genes and their mechanisms of action are laborious basic science studies often involving sophisticated knockin or knockout mouse lines, however, these types of studies are impractical as a high-throughput means to understand the many risk variants that cause complex diseases like coronary artery disease (CAD). As a solution, we developed a streamlined, data-driven informatics pipeline to gain mechanistic insights on complex genetic loci. The pipeline begins by understanding the SNPs in a given locus in terms of their relative location and linkage disequilibrium relationships, and then identifies nearby expression quantitative trait loci (eQTLs) to determine their relative independence and the likely tissues that mediate their disease-causal effects. The pipeline then seeks to understand associations with other disease-relevant genes, disease sub-phenotypes, potential causality (Mendelian randomization), and the regulatory and functional involvement of these genes in gene regulatory co-expression networks (GRNs). Here, we applied this pipeline to understand a cluster of SNPs associated with CAD within and immediately adjacent to the gene encoding HDAC9. Our pipeline demonstrated, and validated, that this locus is causal for CAD by modulation of TWIST1 expression levels in the arterial wall, and by also governing a GRN related to metabolic function in skeletal muscle. Our results reconciled numerous prior studies, and also provided clear evidence that this locus does not govern HDAC9 expression, structure or function. This pipeline should be considered as a powerful and efficient way to understand GWAS risk loci in a manner that better reflects the highly complex nature of genetic risk associated with common disorders.     

Disease association mapping in Drosophila can be replicated in the wild

Association and linkage mapping have become important tools in understanding the genetics of complex traits, including diseases in humans. As the success of association mapping is reduced by small effect sizes and limited power, linkage studies in laboratory-based model systems are still heavily used. But whether the results of these studies can be replicated in natural populations has been questioned. Here, we show that a polymorphism in the gene ref(2)P, which had previously been linked to sigma virus resistance in Drosophila melanogaster under laboratory conditions, also provides resistance against the virus in female flies in a wild population in the field. This genetic association is thus upheld in spite of a known genotype-by-genotype interaction and environmental variation.     

Whole Exome Sequencing of Distant Relatives in Multiplex Families Implicates Rare Variants in Candidate Genes for Oral Clefts

A dozen genes/regions have been confirmed as genetic risk factors for oral clefts in human association and linkage studies, and animal models argue even more genes may be involved. Genomic sequencing studies should identify specific causal variants and may reveal additional genes as influencing risk to oral clefts, which have a complex and heterogeneous etiology. We conducted a whole exome sequencing (WES) study to search for potentially causal variants using affected relatives drawn from multiplex cleft families. Two or three affected second, third, and higher degree relatives from 55 multiplex families were sequenced. We examined rare single nucleotide variants (SNVs) shared by affected relatives in 348 recognized candidate genes. Exact probabilities that affected relatives would share these rare variants were calculated, given pedigree structures, and corrected for the number of variants tested. Five novel and potentially damaging SNVs shared by affected distant relatives were found and confirmed by Sanger sequencing. One damaging SNV in CDH1, shared by three affected second cousins from a single family, attained statistical significance (P = 0.02 after correcting for multiple tests). Family-based designs such as the one used in this WES study offer important advantages for identifying genes likely to be causing complex and heterogeneous disorders.     

Genetics of LDL particle heterogeneity: from genetic epidemiology to DNA-based variations

Substantial evidence exists suggesting that small, dense LDL particles are associated with an increased risk of coronary heart disease. This disease-related risk factor is recognized to be under both genetic and environmental influences. Several studies have been conducted to elucidate the genetic architecture underlying this trait, and a review of this literature seems timely. The methods and strategies used to determine its genetic component and to identify the genes have greatly changed throughout the years owing to the progress made in genetic epidemiology and the influence of the Human Genome Project. Heritability studies, complex segregation analyses, candidate gene linkage and association studies, genome-wide linkage scans, and animal models are all part of the arsenal to determine the susceptibility genes. The compilation of these studies clearly revealed the complex genetic nature of LDL particles. This work is an attempt to summarize the growing evidence of genetic control on LDL particle heterogeneity with the aim of providing a concise overview in one read.     

CRISPR/Cas9 genome editing demonstrates functionality of the autoimmunity-associated SNP rs12946510

Genome-wide association studies (GWAS) map genetic associations of complex traits with precision limited to a linkage disequilibrium group. To translate GWAS results into new understanding of disease mechanisms, individual causative polymorphisms and their target genes should be identified. CRISPR/Cas9 genome editing can be used to create isogenic cell lines bearing alternative genotypes of candidate single-nucleotide polymorphisms to test their causality and to reveal gene targets. An intergenic polymorphism rs12946510 is associated with multiple sclerosis, inflammatory bowel disease and asthma. We created sublines of the T-helper cell line bearing alternative genotypes of rs12946510 and showed that its risk (“T”) allele is associated with lower expression of IKZF3 and ORMDL3 genes and reduced cell activation. Our editing procedure can become an effective tool for discovering new genes involved in pathogenesis of complex diseases.     

Binding of the Covalent Flavin Assembly Factor to the Flavoprotein Subunit of Complex II

Escherichia coli harbors two highly conserved homologs of the essential mitochondrial respiratory complex II (succinate:ubiquinone oxidoreductase). Aerobically the bacterium synthesizes succinate:quinone reductase as part of its respiratory chain, whereas under microaerophilic conditions, the quinol:fumarate reductase can be utilized. All complex II enzymes harbor a covalently bound FAD co-factor that is essential for their ability to oxidize succinate. In eukaryotes and many bacteria, assembly of the covalent flavin linkage is facilitated by a small protein assembly factor, termed SdhE in E. coli. How SdhE assists with formation of the covalent flavin bond and how it binds the flavoprotein subunit of complex II remain unknown. Using photo-cross-linking, we report the interaction site between the flavoprotein of complex II and the SdhE assembly factor. These data indicate that SdhE binds to the flavoprotein between two independently folded domains and that this binding mode likely influences the interdomain orientation. In so doing, SdhE likely orients amino acid residues near the dicarboxylate and FAD binding site, which facilitates formation of the covalent flavin linkage. These studies identify how the conserved SdhE assembly factor and its homologs participate in complex II maturation.     

Stability of exploratory multivariate data modeling in longitudinal data

Exploratory data-driven multivariate analysis provides a means of investigating underlying structure in complex data. To explore the stability of multivariate data modeling, we have applied a common method of multivariate modeling (factor analysis) to the Genetic Analysis Workshop 13 (GAW13) Framingham Heart Study data. Given the longitudinal nature of the data, multivariate models were generated independently for a number of different time points (corresponding to cross-sectional clinic visits for the two cohorts), and compared. In addition, each multivariate model was used to generate factor scores, which were then used as a quantitative trait in variance component-based linkage analysis to investigate the stability of linkage signals over time. We found surprisingly good correlation between factor models (i.e., predicted factor structures), maximum LOD scores, and locations of maximum LOD scores (0.81< rho <0.94 for factor scores; rho >0.99 for peak locations; and 0.67< rho <0.93 for peak LOD scores). Furthermore, the regions implicated by linkage analysis with these factor scores have also been observed in other studies, further validating our exploratory modeling.     

The roles of ADIPOQ genetic variations in cancer risk: evidence from published studies

Adiponectin produced by adipose tissue, which is involved in complex diseases related to obesity, such as cancer. Genetic variations in ADIPOQ are thought to influence the activity of adiponectin, thus relating to cancer occurrence. However, epidemiological results were inconsistent. To examine this controversy, we assessed reported studies of association between ADIPOQ polymorphisms and cancer risk. Relevant studies were selected by PUBMED, EMBASE update to January 12th, 2012. According to the acceptance and exclusion criteria, 15 studies involved three polymorphisms (rs266729, rs2241766, rs1501299) of ADIPOQ were included. Summary odds ratio (ORs) and 95 % confidence intervals (CIs) were calculated using random-effect or fixed-effect models based on the heterogeneity of included studies. A total of 15 case–control studies related rs266729 (5,615 cases and 6,425 controls), rs2241766 (5,318 cases and 6,118 controls) and rs1501299 (3,751 cases and 5,104 controls) were included to analyze the ADIPOQ polymorphisms and cancer risk. For rs1501299, T allele was associated with decreased cancer risk. In addition, cancer type subgroup analysis revealed T allele was associated with decreased colorectal and prostate cancer risk. Ethnicity subgroup analysis observed a decreased risk in both Asian and Caucasian descendents. As to rs2241766, a borderline decreased cancer risk was observed. This meta-analysis indicated T allele of rs1501299 was an obvious protection factor for cancer risk, and G allele of rs2241766 was a potential protection factor for cancer risk, especially in Caucasian descendents. Further studies should be performed to clarify the roles of ADIPOQ polymorphisms in the cancer risk.     

Ionizing radiation and genetic risks: VI. Chronic multifactorial diseases: a review of epidemiological and genetical aspects of coronary heart disease,essential hypertension and diabetes mellitus

This paper provides a broad overview of the epidemiological and genetical aspects of common multifactorial diseases in man with focus on three well-studied ones, namely, coronary heart disease (CHD), essential hypertension (EHYT) and diabetes mellitus (DM). In contrast to mendelian diseases, for which a mutant gene either in the heterozygous or homozygous condition is generally sufficient to cause disease, for most multifactorial diseases, the concepts of `genetic susceptibility' and `risk factors' are more appropriate. For these diseases, genetic susceptibility is heterogeneous. The well-studied diseases such as CHD permit one to conceptualize the complex relationships between genotype and phenotype for chronic multifactorial diseases in general, namely that allelic variations in genes, through their products interacting with environmental factors, contribute to the quantitative variability of biological risk factor traits and thus ultimately to disease outcome. Two types of such allelic variations can be distinguished, namely those in genes whose mutant alleles have (i) small to moderate effects on the risk factor trait, are common in the population (polymorphic alleles) and therefore contribute substantially to the variability of biological risk factor traits and (ii) profound effects, are rare in the population and therefore contribute far less to the variability of biological risk factor traits. For all the three diseases considered in this review, a positive family history is a strong risk factor. CHD is one of the major contributors to mortality in most industrialized countries. Evidence from epidemiological studies, clinical correlations, genetic hyperlipidaemias etc., indicate that lipids play a key role in the pathogenesis of CHD. The known lipid-related risk factors include: high levels of low density lipoprotein cholesterol, low levels of high density lipoprotein cholesterol, high apoB levels (the major protein fraction of the low density lipoprotein particles) and elevated levels of Lp(a) lipoprotein. Among the risk factors which are not related to lipids are: high levels of homocysteine, low activity of paraoxonase and possibly also elevated plasma fibrinogen levels. In addition to the above, hypertension, diabetes and obesity (which themselves have genetic determinants) are important risk factors for CHD. Among the environmental risk factors are: high dietary fat intake, smoking, stress, lack of exercise etc. About 60% of the variability of the plasma cholesterol is genetic in origin. While a few genes have been identified whose mutant alleles have large effects on this trait (e.g., LDLR, familial defective apoB-100), variability in cholesterol levels among individuals in most families is influenced by allelic variation in many genes (polymorphisms) as well as environmental exposures. A proportion of this variation can be accounted for by two alleles of the apoE locus that increase (ϵ4) and decrease (ϵ2) cholesterol levels, respectively. A polymorphism at the apoB gene (XbaI) also has similar effects, but is probably not mediated through lipids. High density lipoprotein cholesterol levels are genetically influenced and are related to apoA1 and hepatic lipase (LIPC) gene functions. Mutations in the apoA1 gene are rare and there are data which suggest a role of allelic variation at or linked LIPC gene in high density lipoprotein cholesterol levels. Polymorphism at the apoA1–C3 loci is often associated with hypertriglyceridemia. The apo(a) gene which codes for Lp(a) is highly polymorphic, each allele determining a specific number of multiple tandem repeats of a unique coding sequence known as Kringle 4. The size of the gene correlates with the size of the Lp(a) protein. The smaller the size of the Lp(a) protein, the higher are the Lp(a) levels. Hyperhomocyst(e)inemia is a risk factor for myocardial infarction, stroke and peripheral vascular disease, but the precise nature and intensity of this association, the biochemical mechanisms involved and the role of environmental factors remain to be fully elucidated. Recently, it has been suggested that polymorphisms in genes that code for paraoxonase may need to be added to the list of genetic risk factors for CHD. There are suggestions that high plasma fibrinogen levels (which is exacerbated by smoking which also lowers high density lipoprotein cholesterol levels) may constitute yet another risk factor for CHD. Essential hypertension (EHYT) affects some 10–25% of the people of the industrial world. Its clinical relevance stems from the fact that it is one of the major risk factors for cardiovascular and renal diseases, especially, stroke, coronary heart disease and end-stage renal disease. The role of genetic factors in EHYT is clearly indicated by family studies in which correlations in blood pressure levels have been studied. The variations in the range and magnitude of these correlations however suggest that other, environmental factors must play an important role and which vary from individual to individual and population to population. No major genes controlling blood pressure have been identified. However during the past five years or so, linkage and association studies have shown that there are at least three gene loci, polymorphism at which may contribute to EHYT: these include the AGT, AT1 and ACE genes. Additionally, the molecular basis of three rare mendelian disorders associated with hypertension, namely those involved in glucocorticosteroid-remediable aldosteronism (GRA), Liddle syndrome and apparent mineralocorticosteroid excess (AME) have been delineated. On the basis of clinical phenotypes, four types of diabetes mellitus are distinguished, of which insulin-dependent diabetes melltius (IDDM) and non-insulin-dependent diabetes mellitus (NIDDM) have been the subject of extensive studies. IDDM is a group of heterogeneous diseases probably resulting from exposure to some environmental agent(s) in those individuals with a genetically-determined susceptibility. IDDM is the result of the destruction of insulin-producing β-cells of the pancreas, principally by immunologically-mediated (autoimmune) mechanisms. The major defined risk factor is genetic susceptibility: apart from IDDM1 (linked to the HLA complex) and IDDM2 (in the insulin gene region) at least 10 other genes are involved, mutations at which cause susceptibility to IDDM. There is recent evidence for the possible involvement of an endogenous retrovirus in the aetiology of acute onset IDDM. NIDDM is a very common disease and its prevalence varies in different populations. As in the case of IDDM, its major determinant is genetic susceptibility. Compared to IDDM, the concordance rates in monozygotic twins and risks to first-degree relatives are higher. With the exception of MODY subtype with earlier onset, most cases have onset in middle or late life. The known geographical variations in the prevalence and studies of migrant populations suggest that environmental factors might also be important. The number of genes mutations at which cause susceptibility to NIDDM is not yet known and so far, one putative major gene locus has recently been identified in a Mexican–American population. Several candidate genes are currently being investigated. The available data indicate that some of the genes act through inherited susceptibility to insulin resistance and to decreased capacity for insulin secretion. Rare forms are due to dominant mutations i.e., the MODY diabetes and rarer still are forms due to the production of abnormal insulin due to mutations in the insulin gene itself. Finally, a small proportion of diabetes may be due to mutations in the mitochondrial genome. The attributes, risk factors and interrelationships between the three diseases considered in this review clearly show that the task of using this information for reliably predicting the risk of any of these diseases is formidable, even for a scenario of no radiation exposures, not to mention radiation scenarios. Nonetheless, these data provide a useful framework for developing models aimed at quantifying the response of these diseases to an increase in mutation rate due to radiation. One such model is discussed in a later paper of this series.     

Insights into Colon Cancer Etiology via a Regularized Approach to Gene Set Analysis of GWAS Data

Genome-wide association studies (GWAS) have successfully identified susceptibility loci from marginal association analysis of SNPs. Valuable insight into genetic variation underlying complex diseases will likely be gained by considering functionally related sets of genes simultaneously. One approach is to further develop gene set enrichment analysis methods, which are initiated in gene expression studies, to account for the distinctive features of GWAS data. These features include the large number of SNPs per gene, the modest and sparse SNP associations, and the additional information provided by linkage disequilibrium (LD) patterns within genes. We propose a “gene set ridge regression in association studies (GRASS)” algorithm. GRASS summarizes the genetic structure for each gene as eigenSNPs and uses a novel form of regularized regression technique, termed group ridge regression, to select representative eigenSNPs for each gene and assess their joint association with disease risk. Compared with existing methods, the proposed algorithm greatly reduces the high dimensionality of GWAS data while still accounting for multiple hits and/or LD in the same gene. We show by simulation that this algorithm performs well in situations in which there are a large number of predictors compared to sample size. We applied the GRASS algorithm to a genome-wide association study of colon cancer and identified nicotinate and nicotinamide metabolism and transforming growth factor beta signaling as the top two significantly enriched pathways. Elucidating the role of variation in these pathways may enhance our understanding of colon cancer etiology.     

Leprosy as a genetic disease

Leprosy (Hansen??s disease) is a human infectious disease whose etiological agent, Mycobacterium leprae, was identified by G. H. A. Hansen in the 19th century. Despite the high efficacy of multidrug therapy (<0.1% annual relapse rate), transmission is persistent. In 2008, approximately 250,000 new cases were reported to the World Health Organization. Clinically, leprosy presents as either the paucibacillary (1?C5 lesions) or the multibacillary (>5 lesions) subtype, highly reflective of a Th1 (cell-mediated) or Th2 (humoral) host immune response, respectively. Subsequent to Mycobacterium leprae exposure, epidemiological studies (e.g., twin studies and complex segregation analyses) maintain the importance of host genetics in susceptibility to leprosy. The results of genome-wide analyses (linkage and association) and candidate gene studies suggest an independent genetic control over both susceptibility to leprosy per se and development of clinical subtype. Moreover, the emergence of a shared genetic background between leprosy and several inflammatory/autoimmune diseases suggests that leprosy is a suitable model for studying the genetic architecture and subsequent pathogenesis of both infectious and inflammatory/autoimmune diseases. We provide the example of NOD2 (Crohn??s disease gene) and LTA (myocardial infarction gene) and the implication of a common genetic risk factor between these two diseases and leprosy. The value of leprosy as a model disease therefore extends far beyond this ancient disease to common afflictions of the 21st century.     

Haplotypes of single cancer driver genes and their local ancestry in a highly admixed long-lived population of Northeast Brazil

Admixed populations have not been examined in detail in cancer genetic studies. Here, we inferred the local ancestry of cancer-associated single nucleotide polymorphisms (SNPs) and haplotypes of a highly admixed Brazilian population. SNP array was used to genotype 73 unrelated individuals aged 80-102 years. Local ancestry inference was performed by merging genotyped regions with phase three data from the 1000 Genomes Project Consortium using RFmix. The average ancestry tract length was 9.12-81.71 megabases. Strong linkage disequilibrium was detected in 48 haplotypes containing 35 SNPs in 10 cancer driver genes. All together, 19 risk and eight protective alleles were identified in 23 out of 48 haplotypes. Homozygous individuals were mainly of European ancestry, whereas heterozygotes had at least one Native American and one African ancestry tract. Native-American ancestry for homozygous individuals with risk alleles for HNF1B, CDH1, and BRCA1 was inferred for the first time. Results indicated that analysis of SNP polymorphism in the present admixed population has a high potential to identify new ancestry-associated alleles and haplotypes that modify cancer susceptibility differentially in distinct human populations. Future case-control studies with populations with a complex history of admixture could help elucidate ancestry-associated biological differences in cancer incidence and therapeutic outcomes.