Familial Aggregation Analysis Research Articles

P901 A genetic analysis of familial aggregation in Inflammatory Bowel Disease multiplex families

Abstract Background Relatives of patients with inflammatory bowel disease (IBD) have a higher risk to develop IBD than the general population. In some families, even a remarkably high prevalence of disease is found. Here, we aim to determine the role of the known IBD risk loci in familial aggregation of disease, as well as to study if there are common variants specific to familial IBD. Methods Imputed immunochip genotypes of 55 families [157 Crohn’s disease (CD), 29 ulcerative colitis (UC) and 138 unaffected relatives] that have at least three affected, first-degree relatives were used. A sporadic dataset (1705 CD, 917 UC, 873 controls) was used for comparison. For each individual, a polygenic risk score (PRS) was calculated with PRSice based on the IBD summary statistics of de Lange et al (2017), a p-value threshold ≤0.01 and MAF≥0.01. The mean PRS of all relatives of one family is denoted the familial PRS. Family-based association analyses were performed with SAIGE. The significance threshold for association used was p<1e-4. Results As a group, unaffected relatives have a lower PRS than affected relatives (p=1.36e-5, β(se)=-0.60(0.14)), but still higher than unrelated controls (p=2.07e-4, β(se)=0.39(0.11))(fig 1). Twenty-four families have a familial PRS that is higher than the mean PRS of sporadic cases, and seven families have a familial PRS that is lower than the mean PRS of unrelated controls, the low PRS families (fig 2A). In most families, the affected members have a higher mean PRS than the unaffected members (fig 2B). This relationship however is sometimes reversed, especially in the low PRS families. SAIGE found nine variants to be associated with familial IBD (fig 3A, table 1). Two independently associated variants, rs2241130 in IL1RL2 (p=1.19 e-5, β(se)=1.21(0.28)) and rs144641193 in IL1RL1 (p=8.23e-5, β(se)=1.29(0.33)) reside in a known IBD locus (IL18RAP). Some other identified variants were also located in genes previously implicated in IBD, either through GWAS [rs72781786 in PRKCQ (p=2.93e-5, β(se)= -0.95(0.23))], or via functional studies (rs2242601 in EPHA1 and rs2272766 in CTSB). A restricted analysis of the low PRS families identified only one significant variant: rs11579543, located between RPE65 and DEPDC1 (p=6.12e-5, β(se)=-2.71(0.68))(fig 3B, table 1). Conclusion Our analysis indicates that common risk variants play an important role in familial aggregation of disease in many multiplex families. Some families however have a very low polygenic risk, indicating shared environmental factors might be relatively more important, or genetic factors not captured by the score, e.g. rare variants, may have contributed. Also, a few loci are specifically implicated in familial IBD, some related to the immune system, e.g. CLECL1 and CD69.

Familial aggregation analysis offers insight into the heritability of stillbirth risk.

Linked article: This is a mini commentary on Workalemahu et al., pp.454–462 in this issue. To view this article visit https://doi.org/10.1111/1471‐0528.17301

Analysis of familial aggregation using recurrence risk for complex survey data

Familial or family aggregation of a disease is important for studying possible genetic etiology of a disease. A popular and useful measure of family aggregation is recurrence risk. Household health surveys with (family) network sampling, which surveyed individuals report about disease status of themselves and specified relatives, have been shown to be useful for estimating prevalence of diseases and more recently for estimating recurrence risk of disease using nonparametric classical survey methods. Because these surveys have complex sample designs with sample weighting for differential sample selection rates, this paper extends the composite-likelihood estimation and hypothesis of parameters of the quadratic exponential model (QEM) for simple random samples to data from these complex sample designs. In addition, the QEM is extended to simultaneously estimate and test parameters and recurrence risk for multiple family relationships, for comparing recurrence risk across family-level covariates (e.g. race) and utilizing propensity score weighting to adjust for confounding by individual-level covariates (e.g. age). Simulations are used to study the finite sample properties of the parameter estimation, variance estimation and level and power of hypothesis testing based on derived Wald and Quasi-Score tests for these extended QEMs. Finally, our methods are illustrated using the 1976 National Health Interview Survey diabetes data set.

Genetic and Metabolic Determinants of Atrial Fibrillation in a General Population Sample: The CHRIS Study.

Atrial fibrillation (AF) is a supraventricular arrhythmia deriving from uncoordinated electrical activation with considerable associated morbidity and mortality. To expand the limited understanding of AF biological mechanisms, we performed two screenings, investigating the genetic and metabolic determinants of AF in the Cooperative Health Research in South Tyrol study. We found 110 AF cases out of 10,509 general population individuals. A genome-wide association scan (GWAS) identified two novel loci (p-value < 5 × 10−8) around SNPs rs745582874, next to gene PBX1, and rs768476991, within gene PCCA, with genotype calling confirmed by Sanger sequencing. Risk alleles at both SNPs were enriched in a family detected through familial aggregation analysis of the phenotype, and both rare alleles co-segregated with AF. The metabolic screening of 175 metabolites, in a subset of individuals, revealed a 41% lower concentration of lysophosphatidylcholine lysoPC a C20:3 in AF cases compared to controls (p-adj = 0.005). The genetic findings, combined with previous evidence, indicate that the two identified GWAS loci may be considered novel genetic rare determinants for AF. Considering additionally the association of lysoPC a C20:3 with AF by metabolic screening, our results demonstrate the valuable contribution of the combined genomic and metabolomic approach in studying AF in large-scale population studies.

A family-based study to identify genetic biomarkers of fibromyalgia: consideration of patients' subgroups.

Evidence from genome-wide and candidate gene association studies, familial aggregation and linkage analyses demonstrate the genetic contribution to fibromyalgia (FM) disease. This study aimed to identify genetic biomarkers of FM and its related comorbid disorders, by exploring 41 polymorphisms potentially involved in FM pathogenesis in families with at least one patient with FM. Core symptoms were assessed, and blood samples collected from 556 patients with FM and 395 healthy relatives. For the genetic study, a final sample of 401 FM patients and 232 healthy controls was selected, discarding patients with concomitant pathologies and controls with chronic pain. A family-based approach using DFAM test (Plink) and SNPs (single nucleotide polymorphisms) combination analyses to compare FM patients vs. controls were first applied. Second, the genotypic distribution of subgroups of FM patients, stratified by severe vs. mild symptoms of pain, depression and sleep impairment, was considered. No evidence of associations with FM per se were detected, using either a family-based approach or SNPs combination analyses. However, considering the subgroups of FM patients, the SNP rs6454674 (CNR1, cannabinoid receptor 1 gene) was found as a potential genetic marker of FM correlated with depression (p<.001). No significant associations using either the family-based analysis or the SNPs combination tests dissociated FM patients and their healthy relatives. FM patients with and without depression showed a significant difference in the genotypic distribution related to the SNP rs6454674 in the cannabinoid receptor 1 gene (CNR1) indicating that FM is not a homogenous disorder.

Novel HLA-DRB1 alleles contribute risk for disease susceptibility in primary biliary cholangitis.

Primary biliary cholangitis (PBC) is a complex disease with high heritability. We investigated the association between human leukocyte antigen (HLA)-DRB1 alleles and PBC in families and sporadic cases to evaluate the genetic components of the disease. We performed whole exome sequencing in three PBC families. We genotyped HLA-DRB1 and calculated the association between HLA-DRB1 alleles and the encoding amino acid sequences with the clinical features. Ten variants harboured the HLA-DRB1 gene associated with PBC. DRB1×07:01, 14:01 and 14:05 were highly increased in PBC. Ten coding region polymorphisms were associated with PBC that encode the amino acid variants of HLA-DR β54, β59 and β66 located in the peptide-binding site of the MHC molecule. Glutamine at position 54 was confirmed as a risk amino acid, verifying the results of familial aggregation analysis of PBC families. Familial aggregation analysis indicated that HLA-DRB1 is a candidate gene for the risk of disease course. Considering that amino acid variations are critical to peptide-binding properties, they underlie the major component of MHC association with PBC.

Familial genetic and environmental risk profile and high blood pressure event: a prospective cohort of cardio-metabolic and genetic study

Background and aims High blood pressure is the heritable risk factor for cardiovascular diseases. We investigated whether the presence of familial genetic and environmental risk factors are associated with increased risk of high blood pressure. Methods A total of 4,559 individuals from 401 families were included in this study. Familial aggregation analysis was carried out on systolic blood pressure (SBP), diastolic blood pressure (DBP), body mass index (BMI) and waist circumference (WC), and heritability was estimated for SBP and DBP. The association between familial risk factors and blood pressure traits including, incidence of hypertension, SBP and DBP was estimated separately using regression-based two-level Haseman-Elston (HE) method, with individual and familial BMI and WC as environmental exposures and familial genetic profile of known variants as genetic risk factors in 210 index families (≥2 hypertensive cases). Models were adjusted for the two nested sets of covariates. Results During a follow-up of 15 years, the SBP, DBP, BMI and WC were highly correlated in inter class of mother-offspring and intraclass of sister-sister with heritability of 30 and 25% for DBP and SBP, respectively. Among index families, those whose members with higher familial BMI or WC had significantly increased risk of hypertension and consistent, strong signals of rs2493134 (AGT) linked with SBP and DBP, rs976683 (NLGN1) linked with SBP and HTN, and epistasis of rs2021783 (TNXB) and known genetic variants linked with all blood pressure traits. Conclusions Findings from this study show that familial genetic and environmental risk profile increase risk for high blood pressure beyond the effect of the individuals’ own risk factors.

Familial aggregation analysis of cognitive performance in early-onset bipolar disorder.

We analysed the familial aggregation (familiality) of cognitive dimensions and explored their role as liability markers for early-onset bipolar disorder (EOBD). The sample comprised 99 subjects from 26 families, each with an offspring diagnosed with EOBD. Four cognitive dimensions were assessed: reasoning skills; attention and working memory; memory; and executive functions. Their familiality was investigated in the total sample and in a subset of healthy relatives. The intra-family resemblance score (IRS), a family-based index of the similarity of cognitive performance among family members, was calculated. Familiality was detected for the attention and working memory (AW) dimension in the total sample (ICC = 0.37, p = 0.0004) and in the subsample of healthy relatives (ICC = 0.37, p = 0.016). The IRS reflected that there are families with similar AW mean scores (either high or low) and families with heterogeneous scores. Families with the most common background for the AW dimension (IRS > 0) were selected and dichotomized in two groups according to the mean family AW score. This allowed differentiating families whose members had similar high scores than those with similar low scores: both patients (t = -4.82, p = 0.0005) and relatives (t = -5.04, p < 0.0001) of the two groups differed in their AW scores. AW dimension showed familial aggregation, suggesting its putative role as a familial vulnerability marker for EOBD. The IRS estimation allowed the identification of families with homogeneous scores for this dimension. This represents a first step towards the investigation of the underlying mechanisms of AW dimension and the identification of etiological subgroups.

Familial Aggregation and Heritability of Obstructive Sleep Apnea Using Children Probands.

Previous studies suggest the presence of familial aggregation of obstructive sleep apnea (OSA) in adults. However, similar data on childhood OSA are limited. This family study aimed to investigate the heritability and familial aggregation of childhood OSA and to examine whether significant differences existed between patients of normal weight and overweight. Children aged 6 to 18 years were recruited as probands either from attendants to sleep clinic (with habitual snoring) or the community (without habitual snoring). Parents and siblings of the probands were also invited to participate. All participants underwent nocturnal sleep study. A total of 229 probands took part, of whom 33 had moderate to severe OSA, 70 had mild disease, and 126 had no OSA. A total of 412 relatives were also recruited. Although the overall heritability of obstructive apnea-hypopnea index (OAHI) was not significant (h² ± SE = 0.03 ± 0.09, P = .37), it was significant in overweight individuals on subgroup analysis (h² ± SE = 0.43 ± 0.24, P = .032). Significant interaction effect of overweight was demonstrated in both heritability and familial aggregation analyses. Bivariate genetic analysis found that the genetic correlation between OAHI and body mass index in overweight individuals (ρg ± SE = 0.63 ± 0.18) was significantly different from both 0 (P = .005) and 1 (P = .025). The differential results of heritability and familial aggregation of OSA in normal weight and overweight subgroups substantiated the recommendation of separating childhood OSA into normal weight and overweight subtypes. In the overweight subgroup, there may be obesity-independent components involved in the genetic variance of OAHI, although a significant proportion of the genetic variance is shared with obesity.

High prevalence and familial aggregation of keratoconus in an Iranian rural population: a population-based study.

The objective of this study was to determine the prevalence of keratoconus and the potential effect of genetic and environmental factors on its prevalence in households living in rural areas of Iran in a large population-based study. The present cross-sectional study was performed in two Iranian rural populations. Two rural areas were randomly selected in the southwest and north of Iran. All individuals over one year of age were invited to participate in the study. The study population underwent a thorough eye examination, including visual acuity measurement, refraction, slit lamp biomicroscopy, and Scheimpflug imaging. The diagnosis of keratoconus was made based on Pentacam-specific criteria, tomographic maps, and clinical findings. After detecting keratoconus cases, its prevalence in the study population was reported as a percentage with a 95% confidence interval (CI). For familial aggregation analysis, the odds ratios of keratoconus and its more severe types were calculated in different family relationships (siblings, parents-offspring, spouses) using second order generalised estimating equation. Of the 3851 eligible individuals, 3314 subjects participated in the study. After applying the exclusion criteria, data from 2667 subjects was used in the analysis. The prevalence of keratoconus in the present population was 4% (95% CI: 3-4). The odds of keratoconus were significantly higher in males (OR = 2.30, p = 0.032). To investigate the familial aggregation of keratoconus, we only evaluated families from which at least two members participated in the study. So, 403 families (1452 participants) were evaluated. Our results showed a higher odds ratio for the sibling pairs compare to parent-offspring pairs and as reported, the odds ratio of the spouses was less than 1.0. Our findings showed a relatively high prevalence and familial aggregation of keratoconus in rural areas of Iran, independent of age, sex, and place of residence. This aggregation may be due to heredity or the effect of undetermined shared environmental factors.

Familial aggregation and linkage analysis with covariates for metabolic syndrome risk factors

BackgroundMechanisms of metabolic syndrome (MetS) causation are complex, genetic and environmental factors are important factors for the pathogenesis of MetS In this study, we aimed to evaluate familial and genetic influences on metabolic syndrome risk factor and also assess association between FTO (rs1558902 and rs7202116) and CETP(rs1864163) genes' single nucleotide polymorphisms (SNP) with low HDL_C in the Tehran Lipid and Glucose Study (TLGS). Materials and methodsThe design was a cross-sectional study of 1776 members of 227 randomly-ascertained families. Selected families contained at least one affected metabolic syndrome and at least two members of the family had suffered a loss of HDL_C according to ATP III criteria.In this study, after confirming the familial aggregation with intra-trait correlation coefficients (ICC) of Metabolic syndrome (MetS) and the quantitative lipid traits, the genetic linkage analysis of HDL_C was performed using conditional logistic method with adjusted sex and age. ResultsThe results of the aggregation analysis revealed a higher correlation between siblings than between parent-offspring pairs representing the role of genetic factors in MetS. In addition, the conditional logistic model with covariates showed that the linkage results between HDL_C and three marker, rs1558902, rs7202116 and rs1864163 were significant. ConclusionsIn summary, a high risk of MetS was found in siblings confirming the genetic influences of metabolic syndrome risk factor. Moreover, the power to detect linkage increases in the one parameter conditional logistic model regarding the use of age and sex as covariates.

Linkage and related analyses of Barrett's esophagus and its associated adenocarcinomas.

BackgroundFamilial aggregation and segregation analysis studies have provided evidence of a genetic basis for esophageal adenocarcinoma (EAC) and its premalignant precursor, Barrett's esophagus (BE). We aim to demonstrate the utility of linkage analysis to identify the genomic regions that might contain the genetic variants that predispose individuals to this complex trait (BE and EAC).MethodsWe genotyped 144 individuals in 42 multiplex pedigrees chosen from 1000 singly ascertained BE/EAC pedigrees, and performed both model‐based and model‐free linkage analyses, using S.A.G.E. and other software. Segregation models were fitted, from the data on both the 42 pedigrees and the 1000 pedigrees, to determine parameters for performing model‐based linkage analysis. Model‐based and model‐free linkage analyses were conducted in two sets of pedigrees: the 42 pedigrees and a subset of 18 pedigrees with female affected members that are expected to be more genetically homogeneous. Genome‐wide associations were also tested in these families.ResultsLinkage analyses on the 42 pedigrees identified several regions consistently suggestive of linkage by different linkage analysis methods on chromosomes 2q31, 12q23, and 4p14. A linkage on 15q26 is the only consistent linkage region identified in the 18 female‐affected pedigrees, in which the linkage signal is higher than in the 42 pedigrees. Other tentative linkage signals are also reported.ConclusionOur linkage study of BE/EAC pedigrees identified linkage regions on chromosomes 2, 4, 12, and 15, with some reported associations located within our linkage peaks. Our linkage results can help prioritize association tests to delineate the genetic determinants underlying susceptibility to BE and EAC.

FamAgg: an R package to evaluate familial aggregation of traits in large pedigrees.

Summary: Familial aggregation analysis is the first fundamental step to perform when assessing the extent of genetic background of a disease. However, there is a lack of software to analyze the familial clustering of complex phenotypes in very large pedigrees. Such pedigrees can be utilized to calculate measures that express trait aggregation on both the family and individual level, providing valuable directions in choosing families for detailed follow-up studies. We developed FamAgg, an open source R package that contains both established and novel methods to investigate familial aggregation of traits in large pedigrees. We demonstrate its use and interpretation by analyzing a publicly available cancer dataset with more than 20 000 participants distributed across approximately 400 families.Availability and implementation: The FamAgg package is freely available at the Bioconductor repository, http://www.bioconductor.org/packages/FamAgg.Contact: Christian.Weichenberger@eurac.eduSupplementary information: Supplementary data are available at Bioinformatics online.

Genetics of leprosy: Expected—and unexpected—developments and perspectives

A solid body of evidence produced over decades of intense research supports the hypothesis that leprosy phenotypes are largely dependent on the genetic characteristics of the host. The early evidence of a major gene effect controlling susceptibility to leprosy came from studies of familial aggregation, twins, and complex segregation analysis. Later, linkage and association analysis, first applied to the investigation of candidate genes and chromosomal regions and more recently, to genome-wide scans, have revealed several HLA and non-HLA gene variants as risk factors for leprosy phenotypes such as disease per se, its clinical forms, and leprosy reactions. In addition, powerful, hypothesis-free strategies such as genome-wide association studies have led to an exciting, unexpected development: Leprosy susceptibility genes seem to be shared with Crohn’s and Parkinson’s disease. Today, a major challenge is to find the exact variants causing the biological effect underlying the genetic associations. New technologies, such as Next Generation Sequencing—that allows, for the first time, the cost- and time-effective sequencing of a complete human genome—hold the promise to reveal such variants; thus, strategies can be developed to study the functional impact of these variants in the context of infection, hopefully leading to the development of new targets for leprosy treatment and prevention.

Influence of technology in genetic epidemiology

AbstractGenetic epidemiology is the study of genetic factors and their influence on health and disease. Traditionally, these studies have been based on familial aggregation, segregation, or linkage analysis, mainly allowing the study of monogenic disorders. Advances in biotechnology have made techniques such as genome-wide association studies and next-generation sequencing possible, allowing more complex studies. In addition to the completion of large consortia projects, such as the Human Genome Project, ENCODE, and the 1000 Genome Project, these techniques make it possible to explain a higher proportion of the heritability in polygenic disorders compared to previous techniques. Here, we provide an overview of approaches to genetic epidemiology and how technological improvements have influenced experimentation in this area. These improvements have led genetic epidemiology to unprecedented advances, being excellent tools for understanding the genetic variability underlying complex phenotypes.

Association Study between Polycystic Ovarian Syndrome and the Susceptibility Genes Polymorphisms in Hui Chinese Women.

IntroductionPolycystic ovary syndrome (PCOS) is one of the most common endocrine-metabolic disorders. Evidence of familial aggregation analysis and different clinical traits among different regions and ethnicities indicated that the pathogenesis of PCOS is associated with multiple genetic and environmental factors. Our previous research had identified three susceptibility loci (rs2479106, DENND1A; rs13405728, LHCGR; rs13429458, THADA) for PCOS in Han Chinese women. The overall aim of this study was to investigate the relationship between three susceptibility gene polymorphisms and PCOS in Hui ethnic women.Methods151 patients with PCOS (case group) and 99 healthy women (control group) were recruited from the Reproductive Medicine Center of the General Hospital of Ningxia Medical University. Clinical data and serum hormone characteristics of case and control groups were collected and analyzed. The three susceptibility single-nucleotide polymorphisms have been replicated in both case and control groups. Gene polymorphisms were detected by direct sequencing after polymerase chain reaction.ResultsThe Body Mass Index, LH, LH/FSH ratio and total testosterone were significantly elevated in PCOS patients compared to control group (P<0.05). The frequencies of genotype and allele in rs13405728 were significantly different between the PCOS and the control groups (P<0.05). Of the SNP rs13405728, the PCOS cases with TT genotype stayed at a higher level of total testosterone, TG and LDL than those with the CC and CT genotypes. In contrary, there was no statistical difference between the two groups for SNP rs13429458 and rs2479106 (P>0.05).ConclusionThe present study suggested that the SNP rs13405728 in the LHCGR gene was associated with PCOS in Hui ethnic women, and its TT genotype characterized with higher level of TT, TG and LDL.

A novel approach for identifying causal models of complex diseases from family data.

Causal models including genetic factors are important for understanding the presentation mechanisms of complex diseases. Familial aggregation and segregation analyses based on polygenic threshold models have been the primary approach to fitting genetic models to the family data of complex diseases. In the current study, an advanced approach to obtaining appropriate causal models for complex diseases based on the sufficient component cause (SCC) model involving combinations of traditional genetics principles was proposed. The probabilities for the entire population, i.e., normal-normal, normal-disease, and disease-disease, were considered for each model for the appropriate handling of common complex diseases. The causal model in the current study included the genetic effects from single genes involving epistasis, complementary gene interactions, gene-environment interactions, and environmental effects. Bayesian inference using a Markov chain Monte Carlo algorithm (MCMC) was used to assess of the proportions of each component for a given population lifetime incidence. This approach is flexible, allowing both common and rare variants within a gene and across multiple genes. An application to schizophrenia data confirmed the complexity of the causal factors. An analysis of diabetes data demonstrated that environmental factors and gene-environment interactions are the main causal factors for type II diabetes. The proposed method is effective and useful for identifying causal models, which can accelerate the development of efficient strategies for identifying causal factors of complex diseases.

Genetic epidemiological analysis of esophageal cancer in high-incidence areas of China.

Genetic epidemiological studies have shown that genetic susceptibility to esophageal cancer (EC) is an important cause of its high incidence within families in some areas of China. The purpose of this study was to obtain evidence of a genetic basis of EC in Xin-an and Xin-xiang counties in China. Familial aggregation and complex segregation analyses were performed of 79 EC families in these counties. The heritability of EC was examined using Falconer's method and complex segregation analysis was conducted with the SEGREG program in Statistical Analysis for Genetic Epidemiology (SAGE version 5.3.1). The results showed that the distribution of EC in families did not fit well into a binomial distribution. The heritability of EC among first-degree and second- degree relatives was 67.0±7.31% and 43.1%±9.80%, respectively, and the summing up powered heritability was 53.2±6.74%. The segregation ratio was 0.045. Complex segregation analysis showed that the genetic model of EC was additive. The current results provide evidence for an inherited propensity to EC in certain high-risk groups in China, and support efforts to identify the genes that confer susceptibility to this disease.

Genetics of leprosy: Expected and unexpected developments and perspectives

A solid body of evidence produced over decades of intense research supports the hypothesis that leprosy phenotypes are largely dependent on the genetic characteristics of the host. The early evidence of a major gene effect controlling susceptibility to leprosy came from studies of familial aggregation, twins, and Complex Segregation Analysis. Later, linkage and association analysis, first applied to the investigation of candidate genes and chromosomal regions and more recently, to genome-wide scans, have revealed several leukocyte antigen complex and nonleukocyte antigen complex gene variants as risk factors for leprosy phenotypes such as disease per se, its clinical forms and leprosy reactions. In addition, powerful, hypothesis-free strategies such as Genome-Wide Association Studies have led to an exciting, unexpected development: Leprosy susceptibility genes seem to be shared with Crohn’s and Parkinson’s diseases. Today, a major challenge is to find the exact variants causing the biological effect underlying the genetic associations. New technologies, such as Next Generation Sequencing that allows, for the first time, the cost and time-effective sequencing of a complete human genome, hold the promise to reveal such variants. Strategies can be developed to study the functional effect of these variants in the context of infection, hopefully leading to the development of new targets for leprosy treatment and prevention.

Chronic Obstructive Pulmonary Disease Genetics: A Review of the Past and a Look Into the Future.

Chronic obstructive pulmonary disease (COPD) affects over 10 million Americans.1 This complex disorder demonstrates many different presentations in a wide variety of patients, and results from a combination of environmental exposures and genetic risk factors. Smoking alone does not result in COPD: not all smokers develop COPD and lung function decline among smokers is highly variable. There is growing evidence for genetic risk factors for COPD: early familial aggregation and linkage analysis studies strongly suggested genetic contributions to COPD, and recent genome-wide association studies have identified several genomic regions that are clearly related to COPD susceptibility. However, despite recent advances in COPD genetics, much of the heritability of COPD remains unexplained, and functional studies are only beginning to elucidate a role for the genetic associations that have been identified. Despite this, the future is bright for understanding the genetics of COPD. Improvements in COPD phenotyping, collaborations among COPD study cohorts, and novel integrative approaches to identifying genetic markers all promise to unravel much of this missing heritability and ultimately lead to improvements in our understanding of COPD susceptibility and treatment.